assignment about problem

Assignment Problem: Meaning, Methods and Variations | Operations Research

After reading this article you will learn about:- 1. Meaning of Assignment Problem 2. Definition of Assignment Problem 3. Mathematical Formulation 4. Hungarian Method 5. Variations.

Meaning of Assignment Problem:

An assignment problem is a particular case of transportation problem where the objective is to assign a number of resources to an equal number of activities so as to minimise total cost or maximize total profit of allocation.

The problem of assignment arises because available resources such as men, machines etc. have varying degrees of efficiency for performing different activities, therefore, cost, profit or loss of performing the different activities is different.

Thus, the problem is “How should the assignments be made so as to optimize the given objective”. Some of the problem where the assignment technique may be useful are assignment of workers to machines, salesman to different sales areas.

Definition of Assignment Problem:

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Suppose there are n jobs to be performed and n persons are available for doing these jobs. Assume that each person can do each job at a term, though with varying degree of efficiency, let c ij be the cost if the i-th person is assigned to the j-th job. The problem is to find an assignment (which job should be assigned to which person one on-one basis) So that the total cost of performing all jobs is minimum, problem of this kind are known as assignment problem.

The assignment problem can be stated in the form of n x n cost matrix C real members as given in the following table:

How to Solve the Assignment Problem: A Complete Guide

Table of Contents

Assignment problem is a special type of linear programming problem that deals with assigning a number of resources to an equal number of tasks in the most efficient way. The goal is to minimize the total cost of assignments while ensuring that each task is assigned to only one resource and each resource is assigned to only one task. In this blog, we will discuss the solution of the assignment problem using the Hungarian method, which is a popular algorithm for solving the problem.

Understanding the Assignment Problem

Before we dive into the solution, it is important to understand the problem itself. In the assignment problem, we have a matrix of costs, where each row represents a resource and each column represents a task. The objective is to assign each resource to a task in such a way that the total cost of assignments is minimized. However, there are certain constraints that need to be satisfied – each resource can be assigned to only one task and each task can be assigned to only one resource.

Solving the Assignment Problem

There are various methods for solving the assignment problem, including the Hungarian method, the brute force method, and the auction algorithm. Here, we will focus on the steps involved in solving the assignment problem using the Hungarian method, which is the most commonly used and efficient method.

Step 1: Set up the cost matrix

The first step in solving the assignment problem is to set up the cost matrix, which represents the cost of assigning a task to an agent. The matrix should be square and have the same number of rows and columns as the number of tasks and agents, respectively.

Step 2: Subtract the smallest element from each row and column

To simplify the calculations, we need to reduce the size of the cost matrix by subtracting the smallest element from each row and column. This step is called matrix reduction.

Step 3: Cover all zeros with the minimum number of lines

The next step is to cover all zeros in the matrix with the minimum number of horizontal and vertical lines. This step is called matrix covering.

Step 4: Test for optimality and adjust the matrix

To test for optimality, we need to calculate the minimum number of lines required to cover all zeros in the matrix. If the number of lines equals the number of rows or columns, the solution is optimal. If not, we need to adjust the matrix and repeat steps 3 and 4 until we get an optimal solution.

Step 5: Assign the tasks to the agents

The final step is to assign the tasks to the agents based on the optimal solution obtained in step 4. This will give us the most cost-effective or profit-maximizing assignment.

Solution of the Assignment Problem using the Hungarian Method

The Hungarian method is an algorithm that uses a step-by-step approach to find the optimal assignment. The algorithm consists of the following steps:

• Subtract the smallest entry in each row from all the entries of the row.
• Subtract the smallest entry in each column from all the entries of the column.
• Draw the minimum number of lines to cover all zeros in the matrix. If the number of lines drawn is equal to the number of rows, we have an optimal solution. If not, go to step 4.
• Determine the smallest entry not covered by any line. Subtract it from all uncovered entries and add it to all entries covered by two lines. Go to step 3.

The above steps are repeated until an optimal solution is obtained. The optimal solution will have all zeros covered by the minimum number of lines. The assignments can be made by selecting the rows and columns with a single zero in the final matrix.

Applications of the Assignment Problem

The assignment problem has various applications in different fields, including computer science, economics, logistics, and management. In this section, we will provide some examples of how the assignment problem is used in real-life situations.

Applications in Computer Science

The assignment problem can be used in computer science to allocate resources to different tasks, such as allocating memory to processes or assigning threads to processors.

Applications in Economics

The assignment problem can be used in economics to allocate resources to different agents, such as allocating workers to jobs or assigning projects to contractors.

Applications in Logistics

The assignment problem can be used in logistics to allocate resources to different activities, such as allocating vehicles to routes or assigning warehouses to customers.

Applications in Management

The assignment problem can be used in management to allocate resources to different projects, such as allocating employees to tasks or assigning budgets to departments.

Let’s consider the following scenario: a manager needs to assign three employees to three different tasks. Each employee has different skills, and each task requires specific skills. The manager wants to minimize the total time it takes to complete all the tasks. The skills and the time required for each task are given in the table below:

The assignment problem is to determine which employee should be assigned to which task to minimize the total time required. To solve this problem, we can use the Hungarian method, which we discussed in the previous blog.

Using the Hungarian method, we first subtract the smallest entry in each row from all the entries of the row:

Next, we subtract the smallest entry in each column from all the entries of the column:

We draw the minimum number of lines to cover all the zeros in the matrix, which in this case is three:

Since the number of lines is equal to the number of rows, we have an optimal solution. The assignments can be made by selecting the rows and columns with a single zero in the final matrix. In this case, the optimal assignments are:

• Emp 1 to Task 3
• Emp 2 to Task 2
• Emp 3 to Task 1

This assignment results in a total time of 9 units.

I hope this example helps you better understand the assignment problem and how to solve it using the Hungarian method.

Solving the assignment problem may seem daunting, but with the right approach, it can be a straightforward process. By following the steps outlined in this guide, you can confidently tackle any assignment problem that comes your way.

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Operations Research

1 Operations Research-An Overview

• History of O.R.
• Approach, Techniques and Tools
• Phases and Processes of O.R. Study
• Typical Applications of O.R
• Limitations of Operations Research
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• O.R. in real world

2 Linear Programming: Formulation and Graphical Method

• General formulation of Linear Programming Problem
• Optimisation Models
• Basics of Graphic Method
• Important steps to draw graph
• Multiple, Unbounded Solution and Infeasible Problems
• Solving Linear Programming Graphically Using Computer
• Application of Linear Programming in Business and Industry

3 Linear Programming-Simplex Method

• Principle of Simplex Method
• Computational aspect of Simplex Method
• Simplex Method with several Decision Variables
• Two Phase and M-method
• Multiple Solution, Unbounded Solution and Infeasible Problem
• Sensitivity Analysis
• Dual Linear Programming Problem

4 Transportation Problem

• Basic Feasible Solution of a Transportation Problem
• Modified Distribution Method
• Stepping Stone Method
• Unbalanced Transportation Problem
• Degenerate Transportation Problem
• Transhipment Problem
• Maximisation in a Transportation Problem

5 Assignment Problem

• Solution of the Assignment Problem
• Unbalanced Assignment Problem
• Problem with some Infeasible Assignments
• Maximisation in an Assignment Problem
• Crew Assignment Problem

6 Application of Excel Solver to Solve LPP

• Building Excel model for solving LP: An Illustrative Example

7 Goal Programming

• Concepts of goal programming
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• The simplex method of goal programming
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8 Integer Programming

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9 Dynamic Programming

• Dynamic Programming Methodology: An Example
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10 Non-Linear Programming

• Solution of a Non-linear Programming Problem
• Convex and Concave Functions
• Kuhn-Tucker Conditions for Constrained Optimisation
• Quadratic Programming
• Separable Programming
• NLP Models with Solver

11 Introduction to game theory and its Applications

• Important terms in Game Theory
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12 Monte Carlo Simulation

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13 Queueing Models

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One of the most well-known combinatorial optimization problems is the assignment problem . Here's an example: suppose a group of workers needs to perform a set of tasks, and for each worker and task, there is a cost for assigning the worker to the task. The problem is to assign each worker to at most one task, with no two workers performing the same task, while minimizing the total cost.

You can visualize this problem by the graph below, in which there are four workers and four tasks. The edges represent all possible ways to assign workers to tasks. The labels on the edges are the costs of assigning workers to tasks.

An assignment corresponds to a subset of the edges, in which each worker has at most one edge leading out, and no two workers have edges leading to the same task. One possible assignment is shown below.

The total cost of the assignment is 70 + 55 + 95 + 45 = 265 .

The next section shows how solve an assignment problem, using both the MIP solver and the CP-SAT solver.

Other tools for solving assignment problems

OR-Tools also provides a couple of other tools for solving assignment problems, which can be faster than the MIP or CP solvers:

• Linear sum assignment solver
• Minimum cost flow solver

However, these tools can only solve simple types of assignment problems. So for general solvers that can handle a wide variety of problems (and are fast enough for most applications), we recommend the MIP and CP-SAT solvers.

Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License , and code samples are licensed under the Apache 2.0 License . For details, see the Google Developers Site Policies . Java is a registered trademark of Oracle and/or its affiliates.

Last updated 2023-01-02 UTC.

Algorithms: The Assignment Problem

One of the interesting things about studying optimization is that the techniques show up in a lot of different areas. The “assignment problem” is one that can be solved using simple techniques, at least for small problem sizes, and is easy to see how it could be applied to the real world.

Assignment Problem

Pretend for a moment that you are writing software for a famous ride sharing application. In a crowded environment, you might have multiple prospective customers that are requesting service at the same time, and nearby you have multiple drivers that can take them where they need to go. You want to assign the drivers to the customers in a way that minimizes customer wait time (so you keep the customers happy) and driver empty time (so you keep the drivers happy).

The assignment problem is designed for exactly this purpose. We start with m agents and n tasks. We make the rule that every agent has to be assigned to a task. For each agent-task pair, we figure out a cost associated to have that agent perform that task. We then figure out which assignment of agents to tasks minimizes the total cost.

Of course, it may be true that m != n , but that’s OK. If there are too many tasks, we can make up a “dummy” agent that is more expensive than any of the others. This will ensure that the least desirable task will be left to the dummy agent, and we can remove that from the solution. Or, if there are too many agents, we can make up a “dummy” task that is free for any agent. This will ensure that the agent with the highest true cost will get the dummy task, and will be idle.

If that last paragraph was a little dense, don’t worry; there’s an example coming that will help show how it works.

There are special algorithms for solving assignment problems, but one thing that’s nice about them is that a general-purpose solver can handle them too. Below is an example, but first it will help to cover a few concepts that we’ll be using.

Optimization Problems

Up above, we talked about making “rules” and minimizing costs. The usual name for this is optimization. An optimization problem is one where we have an “objective function” (which tells us what our goals are) and one or more “constraint functions” (which tell us what the rules are). The classic example is a factory that can make both “widgets” and “gadgets”. Each “widget” and “gadget” earns a certain amount of profit, but it also uses up raw material and time on the factory’s machines. The optimization problem is to determine exactly how many “widgets” and how many “gadgets” to make to maximize profit (the objective) while fitting within the material and time available (the constraints).

If we were to write this simple optimization problem out, it might look like this:

In this case, we have two variables: g for the number of gadgets we make and w for the number of widgets we make. We also have three constraints that we have to meet. Note that they are inequalities; we might not use all the available material or time in our optimal solution.

Just to unpack this a little: in English, the above is saying that we make 45 dollars / euros / quatloos per gadget we make. However, to make a gadget needs 120 lbs of raw material 1, 80 lbs of raw material 2, and 3.8 hours of machine time. So there is a limit on how many gadgets we can make, and it might be a better use of resources to balance gadgets with widgets.

Of course, real optimization problems have many more than two variables and many constraint functions, making them much harder to solve. The easiest kind of optimization problem to solve is linear, and fortunately, the assignment problem is linear.

Linear Programming

A linear program is a kind of optimization problem where both the objective function and the constraint functions are linear. (OK, that definition was a little self-referential.) We can have as many variables as we want, and as many constraint functions as we want, but none of the variables can have exponents in any of the functions. This limitation allows us to apply very efficient mathematical approaches to solve the problem, even for very large problems.

We can state the assignment problem as a linear programming problem. First, we choose to make “i” represent each of our agents (drivers) and “j” to represent each of our tasks (customers). Now, to write a problem like this, we need variables. The best approach is to use “indicator” variables, where xij = 1 means “driver i picks up customer j” and xij = 0 means “driver i does not pick up customer j”.

We wind up with:

This is a compact mathematical way to describe the problem, so again let me put it in English.

First, we need to figure out the cost of having each driver pick up each customer. Then, we can calculate the total cost for any scenario by just adding up the costs for the assignments we pick. For any assignment we don’t pick, xij will equal zero, so that term will just drop out of the sum.

Of course, the way we set up the objective function, the cheapest solution is for no drivers to pick up any customers. That’s not a very good business model. So we need a constraint to show that we want to have a driver assigned to every customer. At the same time, we can’t have a driver assigned to mutiple customers. So we need a constraint for that too. That leads us to the two constraints in the problem. The first just says, if you add up all the assignments for a given driver, you want the total number of assignments for that driver to be exactly one. The second constraint says, if you add up all the assignments to a given customer, you want the total number of drivers assigned to the customer to be one. If you have both of these, then each driver is assigned to exactly one customer, and the customers and drivers are happy. If you do it in a way that minimizes costs, then the business is happy too.

Solving with Octave and GLPK

The GNU Linear Programming Kit is a library that solves exactly these kinds of problems. It’s easy to set up the objective and constraints using GNU Octave and pass these over to GLPK for a solution.

Given some made-up sample data, the program looks like this:

Start with the definition of “c”, the cost information. For this example, I chose to have four drivers and three customers. There are sixteen numbers there; the first four are the cost of each driver to get the first customer, the next four are for the second customer, and the next four are for the third customer. Because we have an extra driver, we add a “dummy” customer at the end that is zero cost. This represents one of the drivers being idle.

The next definition is “b”, the right-hand side of our constraints. There are eight constraints, one for each of the drivers, and one for each of the customers (including the dummy). For each constraint, the right-hand side is 1.

The big block in the middle defines our constraint matrix “a”. This is the most challenging part of taking the mathematical definition and putting it into a form that is usable by GLPK; we have to expand out each constraint. Fortunately, in these kinds of cases, we tend to get pretty patterns that help us know we’re on the right track.

The first line in “a” says that the first customer needs a driver. To see why, remember that in our cost information, the first four numbers are the cost for each driver to get the first customer. With this constraint, we are requiring that one of those four costs be included and therefore that a driver is “selected” for the first customer. The other lines in “a” work similarly; the last four ensure that each driver has an assignment.

Note that the number of rows in “a” matches the number of items in “b”, and the number of columns in “a” matches the number of items in “c”. This is important; GLPK won’t run if this is not true (and our problem isn’t stated right in any case).

Compared to the above, the last few lines are easy.

• “lb” gives the lower bound for each variable.
• “ub” gives the upper bound.
• “ctype” tells GLPK that each constraint is an equality (“strict” as opposed to providing a lower or upper bound).
• “vartype” tells GLPK that these variables are all integers (can’t have half a driver showing up).
• “s” tells GLPK that we want to minimize our costs, not maximize them.

We push all that through a function call to GLPK, and what comes back are two values (along with some other stuff I’ll exclude for clarity):

The first item tells us that our best solution takes 27 minutes, or dollars, or whatever unit we used for cost. The second item tells us the assignments we got. (Note for pedants: I transposed this output to save space.)

This output tells us that customer 1 gets driver 2, customer 2 gets driver 3, customer 3 gets driver 4, and driver 1 is idle. If you look back at the cost data, you can see this makes sense, because driver 1 had some of the most expensive times to the three customers. You can also see that it managed to pick the least expensive pairing for each customer. (Of course, if I had done a better job making up cost data, it might not have picked the least expensive pairing in all cases, because a suboptimal individual pairing might still lead to an overall optimal solution. But this is a toy example.)

Of course, for a real application, we would have to take into consideration many other factors, such as the passage of time. Rather than knowing all of our customers and drivers up front, we would have customers and drivers continually showing up and being assigned. But I hope this simple example has revealed some of the concepts behind optimization and linear programming and the kinds of real-world problems that can be solved.

The assignment problem revisited

• Original Paper
• Published: 16 August 2021
• Volume 16 , pages 1531–1548, ( 2022 )

Cite this article

• Carlos A. Alfaro   ORCID: orcid.org/0000-0001-9783-8587 1 ,
• Sergio L. Perez 2 ,
• Carlos E. Valencia 3 &
• Marcos C. Vargas 1  

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First, we give a detailed review of two algorithms that solve the minimization case of the assignment problem, the Bertsekas auction algorithm and the Goldberg & Kennedy algorithm. It was previously alluded that both algorithms are equivalent. We give a detailed proof that these algorithms are equivalent. Also, we perform experimental results comparing the performance of three algorithms for the assignment problem: the \(\epsilon \) - scaling auction algorithm , the Hungarian algorithm and the FlowAssign algorithm . The experiment shows that the auction algorithm still performs and scales better in practice than the other algorithms which are harder to implement and have better theoretical time complexity.

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Some results on an assignment problem variant

Integer Programming

A Full Description of Polytopes Related to the Index of the Lowest Nonzero Row of an Assignment Matrix

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Alfaro, C.A., Perez, S.L., Valencia, C.E. et al. The assignment problem revisited. Optim Lett 16 , 1531–1548 (2022). https://doi.org/10.1007/s11590-021-01791-4

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Assignment problem

The problem of optimally assigning $ m $ individuals to $ m $ jobs. It can be formulated as a linear programming problem that is a special case of the transport problem :

maximize $ \sum _ {i,j } c _ {ij } x _ {ij } $

$$ \sum _ { j } x _ {ij } = a _ {i} , i = 1 \dots m $$

(origins or supply),

$$ \sum _ { i } x _ {ij } = b _ {j} , j = 1 \dots n $$

(destinations or demand), where $ x _ {ij } \geq 0 $ and $ \sum a _ {i} = \sum b _ {j} $, which is called the balance condition. The assignment problem arises when $ m = n $ and all $ a _ {i} $ and $ b _ {j} $ are $ 1 $.

If all $ a _ {i} $ and $ b _ {j} $ in the transposed problem are integers, then there is an optimal solution for which all $ x _ {ij } $ are integers (Dantzig's theorem on integral solutions of the transport problem).

In the assignment problem, for such a solution $ x _ {ij } $ is either zero or one; $ x _ {ij } = 1 $ means that person $ i $ is assigned to job $ j $; the weight $ c _ {ij } $ is the utility of person $ i $ assigned to job $ j $.

The special structure of the transport problem and the assignment problem makes it possible to use algorithms that are more efficient than the simplex method . Some of these use the Hungarian method (see, e.g., [a5] , [a1] , Chapt. 7), which is based on the König–Egervary theorem (see König theorem ), the method of potentials (see [a1] , [a2] ), the out-of-kilter algorithm (see, e.g., [a3] ) or the transportation simplex method.

In turn, the transportation problem is a special case of the network optimization problem.

A totally different assignment problem is the pole assignment problem in control theory.

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WHAT IS ASSIGNMENT PROBLEM

Assignment Problem is a special type of linear programming problem where the objective is to minimise the cost or time of completing a number of jobs by a number of persons.

The assignment problem in the general form can be stated as follows:

“Given n facilities, n jobs and the effectiveness of each facility for each job, the problem is to assign each facility to one and only one job in such a way that the measure of effectiveness is optimised (Maximised or Minimised).”

Several problems of management has a structure identical with the assignment problem.

Example I A manager has four persons (i.e. facilities) available for four separate jobs (i.e. jobs) and the cost of assigning (i.e. effectiveness) each job to each ...

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Effective problem statements have these 5 components

We’ve all encountered problems on the job. After all, that’s what a lot of work is about. Solving meaningful problems to help improve something. 

Developing a problem statement that provides a brief description of an issue you want to solve is an important early step in problem-solving .

It sounds deceptively simple. But creating an effective problem statement isn’t that easy, even for a genius like Albert Einstein. Given one hour to work on a problem, he’d spend 55 minutes thinking about the problem and five minutes finding solutions. (Or so the story goes.)

Einstein was probably exaggerating to make a point. But considering his success in solving complex problems, we think he was on to something. 

As humans, we’re wired to jump past the problem and go directly to the solution stage. In emergencies, this behavior can be lifesaving, as in leaping out of the way of a speeding car. But when dealing with longer-range issues in the workplace, this can lead to bad decisions or half-baked solutions. 

That’s where problem statements come in handy. They help to meaningfully outline objectives to reach effective solutions. Knowing how to develop a great problem statement is also a valuable tool for honing your management skills .

But what exactly is a problem statement, when should you use one, and how do you go about writing one? In this article, we'll answer those questions and give you some tips for writing effective problem statements. Then you'll be ready to take on more challenges large and small.

What is a problem statement?

First, let’s start by defining a problem statement. 

A problem statement is a short, clear explanation of an issue or challenge that sums up what you want to change. It helps you, team members, and other stakeholders to focus on the problem, why it’s important, and who it impacts. 

A good problem statement should create awareness and stimulate creative thinking . It should not identify a solution or create a bias toward a specific strategy.

Taking time to work on a problem statement is a great way to short-circuit the tendency to rush to solutions. It helps to make sure you’re focusing on the right problem and have a well-informed understanding of the root causes. The process can also help you take a more proactive than reactive approach to problem-solving . This can help position you and your team to avoid getting stuck in constant fire-fighting mode. That way, you can take advantage of more growth opportunities.  

When to use a problem statement

The best time to create a problem statement is before you start thinking of solutions. If you catch yourself or your team rushing to the solution stage when you’re first discussing a problem, hit the brakes. Go back and work on the statement of the problem to make sure everyone understands and agrees on what the real problem is. 

Here are some common situations where writing problem statements might come in handy: 

• Writing an executive summary for a project proposal or research project
• Collaborating   on a cross-functional project with several team members
• Defining the customer issue that a proposed product or service aims to solve
• Using design thinking to improve user experience
• Tackling a problem that previous actions failed to solve 

How to identify a problem statement

Like the unseen body of an iceberg, the root cause of a specific problem isn’t always obvious. So when developing a problem statement, how do you go about identifying the true, underlying problem?

These two steps will help you uncover the root cause of a problem :

• Collect information from the research and previous experience with the problem
• Talk to multiple stakeholders who are impacted by the problem

People often perceive problems differently. Interviewing stakeholders will help you understand the problem from diverse points of view. It can also help you develop some case studies to illustrate the problem. 

Combining these insights with research data will help you identify root causes more accurately. In turn, this methodology will help you craft a problem statement that will lead to more viable solutions. 

What are problem statements used for?

You can use problem statements for a variety of purposes. For an organization, it might be solving customer and employee issues. For the government, it could be improving public health. For individuals, it can mean enhancing their own personal well-being . Generally, problem statements can be used to:

• Identify opportunities for improvement
• Focus on the right problems or issues to launch more successful initiatives – a common challenge in leadership
• Help you communicate a problem to others who need to be involved in finding a solution
• Serve as the basis for developing an action plan or goals that need to be accomplished to help solve the problem
• Stimulate thinking outside the box  and other types of creative brainstorming techniques

3 examples of problem statements

When you want to be sure you understand a concept or tool, it helps to see an example. There can also be some differences in opinion about what a problem statement should look like. For instance, some frameworks include a proposed solution as part of the problem statement. But if the goal is to stimulate fresh ideas, it’s better not to suggest a solution within the problem statement. 

In our experience, an effective problem statement is brief, preferably one sentence. It’s also specific and descriptive without being prescriptive. 

Here are three problem statement examples. While these examples represent three types of problems or goals, keep in mind that there can be many other types of problem statements.        

Example Problem Statement 1: The Status Quo Problem Statement

Example: 

The average customer service on-hold time for Example company exceeds five minutes during both its busy and slow seasons.

This can be used to describe a current pain point within an organization that may need to be addressed. Note that the statement specifies that the issue occurs during the company’s slow time as well as the busy season. This is helpful in performing the root cause analysis and determining how this problem can be solved. 

The average customer service on-hold time for Example company exceeds five minutes during both its busy and slow seasons. The company is currently understaffed and customer service representatives are overwhelmed.

Background:

Example company is facing a significant challenge in managing their customer service on-hold times. In the past, the company had been known for its efficient and timely customer service, but due to a combination of factors, including understaffing and increased customer demand, the on-hold times have exceeded five minutes consistently. This has resulted in frustration and dissatisfaction among customers, negatively impacting the company's reputation and customer loyalty.

Reducing the on-hold times for customer service callers is crucial for Example company. Prolonged waiting times have a detrimental effect on customer satisfaction and loyalty, leading to potential customer churn and loss of revenue. Additionally, the company's declining reputation in terms of customer service can have a lasting impact on its competitive position in the market. Addressing this problem is of utmost importance to improve customer experience and maintain a positive brand image.

Objectives:

The primary objective of this project is to reduce the on-hold times for customer service callers at Example company. The specific objectives include:

• Analyzing the current customer service workflow and identifying bottlenecks contributing to increased on-hold times.
• Assessing the staffing levels and resource allocation to determine the extent of understaffing and its impact on customer service.
• Developing strategies and implementing measures to optimize the customer service workflow and reduce on-hold times.
• Monitoring and evaluating the effectiveness of the implemented measures through key performance indicators (KPIs) such as average on-hold time, customer satisfaction ratings, and customer feedback.
• Establishing a sustainable approach to maintain reduced on-hold times, taking into account both busy and slow seasons, through proper resource planning, training, and process improvements.

Example Problem Statement 2: The Destination Problem Statement

Leaders at Example company want to increase net revenue for its premium product line of widgets by 5% for the next fiscal year. 

This approach can be used to describe where an organization wants to be in the future. This type of problem statement is useful for launching initiatives to help an organization achieve its desired state. 

Like creating SMART goals , you want to be as specific as possible. Note that the statement specifies “net revenue” instead of “gross revenue." This will help keep options open for potential actions. It also makes it clear that merely increasing sales is not an acceptable solution if higher marketing costs offset the net gains. 

Leaders at Example company aim to increase net revenue for its premium product line of widgets by 5% for the next fiscal year. However, the company currently lacks the necessary teams to tackle this objective effectively. To achieve this growth target, the company needs to expand its marketing and PR teams, as well as its product development teams, to prepare for scaling. 

Example company faces the challenge of generating a 5% increase in net revenue for its premium product line of widgets in the upcoming fiscal year. Currently, the company lacks the required workforce to drive this growth. Without adequate staff in the marketing, PR, and product development departments, the company's ability to effectively promote, position, and innovate its premium product line will be hindered. To achieve this kind of growth, it is essential that Example company expands teams, enhances capabilities, and strategically taps into the existing pool of loyal customers.

Increasing net revenue for the premium product line is crucial for Example company's overall business success. Failure to achieve the targeted growth rate can lead to missed revenue opportunities and stagnation in the market. By expanding the marketing and PR teams, Example company can strengthen its brand presence, effectively communicate the value proposition of its premium product line, and attract new customers.

Additionally, expanding the product development teams will enable the company to introduce new features and innovations, further enticing existing and potential customers. Therefore, addressing the workforce shortage and investing in the necessary resources are vital for achieving the revenue growth objective.

The primary objective of this project is to increase net revenue for Example company's premium product line of widgets by 5% in the next fiscal year. The specific objectives include:

• Assessing the current workforce and identifying the gaps in the marketing, PR, and product development teams.
• Expanding the marketing and PR teams by hiring skilled professionals who can effectively promote the premium product line and engage with the target audience.
• Strengthening the product development teams by recruiting qualified individuals who can drive innovation, enhance product features, and meet customer demands.
• Developing a comprehensive marketing and PR strategy to effectively communicate the value proposition of the premium product line and attract new customers.
• Leveraging the existing base of loyal customers to increase repeat purchases, referrals, and brand advocacy.
• Allocating sufficient resources, both time and manpower, to support the expansion and scaling efforts required to achieve the ambitious revenue growth target.
• Monitoring and analyzing key performance indicators (KPIs) such as net revenue, customer acquisition, customer retention, and customer satisfaction to measure the success of the growth initiatives.
• Establishing a sustainable plan to maintain the increased revenue growth beyond the next fiscal year by implementing strategies for continuous improvement and adaptation to market dynamics.

Example Problem Statement 3 The Stakeholder Problem Statement

In the last three quarterly employee engagement surveys , less than 30% of employees at Eample company stated that they feel valued by the company. This represents a 20% decline compared to the same period in the year prior. 

This strategy can be used to describe how a specific stakeholder group views the organization. It can be useful for exploring issues and potential solutions that impact specific groups of people. 

Note the statement makes it clear that the issue has been present in multiple surveys and it's significantly worse than the previous year. When researching root causes, the HR team will want to zero in on factors that changed since the previous year.

In the last three quarterly employee engagement surveys, less than 30% of employees at the Example company stated that they feel valued by the company. This indicates a significant decline of 20% compared to the same period in the previous year.

The company aspires to reduce this percentage further to under 10%. However, achieving this goal would require filling specialized roles and implementing substantial cultural changes within the organization.

Example company is facing a pressing issue regarding employee engagement and perceived value within the company. Over the past year, there has been a notable decline in the percentage of employees who feel valued. This decline is evident in the results of the quarterly employee engagement surveys, which consistently show less than 30% of employees reporting a sense of value by the company.

This decline of 20% compared to the previous year's data signifies a concerning trend. To address this problem effectively, Example company needs to undertake significant measures that go beyond superficial changes and necessitate filling specialized roles and transforming the company culture.

Employee engagement and a sense of value are crucial for organizational success. When employees feel valued, they tend to be more productive, committed, and motivated. Conversely, a lack of perceived value can lead to decreased morale, increased turnover rates, and diminished overall performance.

By addressing the decline in employees feeling valued, Example company can improve employee satisfaction, retention, and ultimately, overall productivity. Achieving the desired reduction to under 10% is essential to restore a positive work environment and build a culture of appreciation and respect.

The primary objective of this project is to increase the percentage of employees who feel valued by Example company, aiming to reduce it to under 10%. The specific objectives include:

• Conducting a comprehensive analysis of the factors contributing to the decline in employees feeling valued, including organizational policies, communication practices, leadership styles, and cultural norms.
• Identifying and filling specialized roles, such as employee engagement specialists or culture change agents, who can provide expertise and guidance in fostering a culture of value and appreciation.
• Developing a holistic employee engagement strategy that encompasses various initiatives, including training programs, recognition programs, feedback mechanisms, and communication channels, to enhance employee value perception.
• Implementing cultural changes within the organization that align with the values of appreciation, respect, and recognition, while fostering an environment where employees feel valued.
• Communicating the importance of employee value and engagement throughout all levels of the organization, including leadership teams, managers, and supervisors, to ensure consistent messaging and support.
• Monitoring progress through regular employee surveys, feedback sessions, and key performance indicators (KPIs) related to employee satisfaction, turnover rates, and overall engagement levels.
• Providing ongoing support, resources, and training to managers and supervisors to enable them to effectively recognize and appreciate their teams and foster a culture of value within their respective departments.
• Establishing a sustainable framework for maintaining high employee value perception in the long term, including regular evaluation and adaptation of employee engagement initiatives to address evolving needs and expectations.

What are the 5 components of a problem statement?

In developing a problem statement, it helps to think like a journalist by focusing on the five Ws: who, what, when, where, and why or how. Keep in mind that every statement may not explicitly include each component. But asking these questions is a good way to make sure you’re covering the key elements:

• Who: Who are the stakeholders that are affected by the problem?
• What: What is the current state, desired state, or unmet need? 
• When: When is the issue occurring or what is the timeframe involved?
• Where: Where is the problem occurring? For example, is it in a specific department, location, or region?
• Why: Why is this important or worth solving? How is the problem impacting your customers, employees, other stakeholders, or the organization? What is the magnitude of the problem? How large is the gap between the current and desired state? 

How do you write a problem statement?

There are many frameworks designed to help people write a problem statement. One example is outlined in the book, The Conclusion Trap: Four Steps to Better Decisions, ” by Daniel Markovitz. A faculty member at the Lean Enterprise Institute, the author uses many case studies from his work as a business consultant.

To simplify the process, we’ve broken it down into three steps:

1. Gather data and observe

Use data from research and reports, as well as facts from direct observation to answer the five Ws: who, what, when, where, and why. 

Whenever possible, get out in the field and talk directly with stakeholders impacted by the problem. Get a firsthand look at the work environment and equipment. This may mean spending time on the production floor asking employees questions about their work and challenges. Or taking customer service calls to learn more about customer pain points and problems your employees may be grappling with.    

2. Frame the problem properly  

A well-framed problem will help you avoid cognitive bias and open avenues for discussion. It will also encourage the exploration of more options.

A good way to test a problem statement for bias is to ask questions like these:

3. Keep asking why (and check in on the progress)

When it comes to problem-solving, stay curious. Lean on your growth mindset to keep asking why — and check in on the progress. 

Asking why until you’re satisfied that you’ve uncovered the root cause of the problem will help you avoid ineffective band-aid solutions.

Refining your problem statements

When solving any sort of problem, there’s likely a slew of questions that might arise for you. In order to holistically understand the root cause of the problem at hand, your workforce needs to stay curious. 

An effective problem statement creates the space you and your team need to explore, gain insight, and get buy-in before taking action.

If you have embarked on a proposed solution, it’s also important to understand that solutions are malleable. There may be no single best solution. Solutions can change and adapt as external factors change, too. It’s more important than ever that organizations stay agile . This means that interactive check-ins are critical to solving tough problems. By keeping a good pulse on your course of action, you’ll be better equipped to pivot when the time comes to change. 

BetterUp can help. With access to virtual coaching , your people can get personalized support to help solve tough problems of the future.

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Madeline Miles

Madeline is a writer, communicator, and storyteller who is passionate about using words to help drive positive change. She holds a bachelor's in English Creative Writing and Communication Studies and lives in Denver, Colorado. In her spare time, she's usually somewhere outside (preferably in the mountains) — and enjoys poetry and fiction.

18 excellent educational podcasts to fuel your love of learning

The future of ai: where does your job stand, 6 ai prompt generator tools to boost your creativity, 20 ai tools to help boost productivity in 2023, 4 benefits of ai and 4 potential disadvantages, how to use 100% of your brain: is it possible, the 10 best work productivity tools to maximize your time, applications of ai: 10 common examples, squirrel how to increase attention span so you get stuff done, similar articles, 10 problem-solving strategies to turn challenges on their head, writing a value statement: your guide to keeping your team aligned, 10 personal brand statements to put all eyes on you, discover 4 types of innovation and how to encourage them, what is organizational structure and why is it important, create smart kpis to strategically grow your business, what is customer satisfaction and how can you improve it, what is a career statement, and should you write one, how to craft an impactful company mission statement, stay connected with betterup, get our newsletter, event invites, plus product insights and research..

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How to write a problem statement: a step-by-step guide

Many great business ideas begin with a crucial problem that needed solving. While product teams and designers may be eager to build solutions, it pays to not rush your product out the door. If you’ve ever heard the phrase “Give me six hours to chop down a tree and I will spend the first four sharpening the axe,” you might understand why.

Instead of immediately switching into solution-mode, there’s value in taking time to understand a problem from all angles. One of the best ways to properly diagnose and solve problems is to write a problem statement.

In this article, we explain what problem statements are, how to write one, and share a few examples.

What is a problem statement?

Problem statements summarize a challenge you want to resolve, its causes, who it impacts, and why that’s important. They often read like a concise overview managers can share with stakeholders and their teams.

Why are problem statements important?

Problem statements help you share details about a challenge facing your team. Instead of rushing to a solution, writing a problem statement enables you to reflect on the challenge and plan your response.

The high-level perspective a problem statement offers lets teams focus on the factors they need to change. Managers also use this top-down vantage to oversee their teams as they work out solutions.

When to use a problem statement

Any time you face a challenge is an opportunity to write a problem statement. You can write a problem statement to improve operations in different contexts. For example, you might use a problem statement to:

• Refine project proposals: Managers write project proposals to solve user issues. Problem statements inform these proposals, shaping their goals, plans, and approaches.
• Develop your product offering: Many startups build their business model on solving a long-standing problem. Problem statements help clarify a company’s mission and core product design .
• Clarify the outcome of solving a problem: Problem statements point out the long-term benefits of solving the issue, which can help you put the problem into context for stakeholders and secure necessary resources.
• Collaborate with multiple teams: You can rally teams around a common goal if you frame it as a shared problem. Collaboration ensures you examine the problem and reach solutions from all possible angles.
• Improve the user experience: Problem statements can identify pain points and ways to enhance a product. When teams act on problem statements, this can improve UX.

What are the elements of a problem statement?

You can break problem statements into a few core elements. While the format of a problem statement is flexible, aim to include the following:

• Gap: the challenge, issue, or pain point you currently face
• Orientation: a description of when and where you found the problem and the trend it creates or follows
• Impact: a measure of your problem’s consequences in cost, time, quality, environment, or personal experience
• Importance: why this problem matters to your organization and customers

How to write a problem statement

Now that you understand the elements of a problem statement, you can write your own in five key steps.

1. Identify the problem

Start by pointing out an issue and gathering data. Put yourself in the support or production environment where the problem arises and try to experience it firsthand. When gathering data, look for trends or overarching themes—they may help you find the root cause of your problem later.

After seeing the problem for yourself, interview others who know about it. Start with employees who run into the problem or offer support for it. In some cases, they may have a design brief with more information on the issue. Beyond that, customer testimonials and stakeholder interviews can lay out the full scope of your problem.

2. Put the problem into context

Describe how the problem impacts customers and stakeholders. Avoid personal bias and focus on developing a clear perspective. This approach helps prioritize the issue and explain why you need to solve it. If customers can't reach the benefits of your product because of an issue, that's a high-priority concern. If you’ve ever conducted design research , this process should feel similar.

You can put a problem into context by asking:

• Does the problem lead to a reputational, financial, or logistical cost?
• Is the main issue a symptom of a greater challenge?
• Has your team already tried to solve this problem? Why didn’t past solutions work?
• What do you and your team definitely know about the current problem?

3. Find the root cause

Ask yourself "why" questions about the problem to find its origin point. Your initial assumptions about a problem might stand in the way, so as you learn more about the issue, don’t be afraid to change how you look at it. You'll get closer to the root cause as you reframe your understanding around these discoveries.

If you need help uncovering the root cause or challenging your initial assumptions, these templates can help:

• The 5 whys template helps you get to the root cause of a problem.
• Reverse brainstorming templates reverse the way you frame problems to find new solutions.
• A DMAIC template lets you define, measure, analyze, improve, and control a problem.
• Mind map templates allow for brainstorming causes, effects, and solutions in a shared space.

4. Describe your ideal outcome

Now that you understand the problem, think about your ideal outcome. Whether you're solving a problem with your product or an internal process, remember to avoid scenarios where you put a Band-Aid on the issue. Even if you can avoid specific symptoms in the short term, letting a core problem go unsolved can lead to other setbacks later.

In some cases, you can describe safeguards that let a process work as intended. You can also write an alternative process that avoids the issue altogether. This ideal outcome will inform your goals and objectives in the next step.

5. Propose a solution and outline its benefits

Finally, your problem statement should include solutions to the problem. Including more than one solution gives stakeholders and your team options for deciding your approach. Note the benefits of each solution, highlighting why it stands a chance of working or how it can save on time and costs.

To ensure you arrive at the best solution, be sure to:

• Ask your team if the proposed solution matches their understanding of the problem.
• Consider more than one solution. Sometimes, you can choose between multiple options or apply more than one solution at once.
• Include long-term financial, intangible, and operational benefits the solution provides.
• Consider whether your solution has blind spots or causes changes that could lead to more issues.

Problem statement examples

Now that you know how to write problem statements, here are some examples.

Example 1: Support ticket wait times

Suppose you’re a support manager at a midsize SaaS company. Ideally, you want to respond to every support request within a few hours. However, your team can’t reach turnaround times fast enough to meet customer expectations. Start by breaking down the elements of your problem statement:

• Gap: Customers have long wait times for their support tickets to get a response.
• Orientation: This problem began in the last few months and has only worsened.
• Impact: Customers aren't happy with their quality of service, and your teams feel burnt out from trying to keep up.
• Importance: Retaining customers with support is essential for sustaining your business.

Now that we’ve laid out the details, we can format it as a problem statement:

• Identify the problem: You have high support ticket turnaround times. Gather data by tracking how the time has lengthened in the past few months and talking to customers about inconsistencies in wait times.
• Put it into context: Customers upset about their wait could switch to competitors. You initially assumed it was seasonal demand rising, but wait times haven’t tapered off, which could cause reputational and financial problems.
• Find the root cause: You initially assumed demand had increased. Support tickets have remained steady, but your AI support designed to solve minor problems has had fewer tickets. This lack of AI support has your teams stretched thin.
• Describe your ideal outcome: AI support should be able to handle more advanced queries. This way, your service teams can focus solely on tickets too advanced for AI.
• Propose a solution: Choose between assigning devs to revamp your AI or investing in a new solution to handle tickets. You can also consider reworking support agents' workflows to focus more on direct customer contact.

Example 2: New feature development

Assume you're a project manager at a tech company. You offer a platform that tracks goals and finds inefficiencies in your programmer's workflows. Your leadership wants to release a tool that lets customers estimate the amount of money earned for each workflow issue they correct. However, you aren't sure you have the resources to implement the feature.

• Gap: You need to create a payoff calculator, but you may not have the necessary resources.
• Orientation: The problem began when you received the assignment. The more time you spend researching the new tool , the less time you have to implement it.
• Impact: Failure to get this feature off the ground will give competitors who offer this tool an advantage.
• Importance: You need this feature to stand out from competitors and for lead generation.

With this information, you can turn it into a problem statement:

• Identify the problem: Your team doesn’t have the resources to design and implement a new feature. Start by interviewing stakeholders and employees who have worked on tools like this—they can explain the issues and solutions that go into adding this feature.
• Put it into context: Not implementing this feature would give competitors an edge and potentially push customers interested in payoff calculators away from your product.
• Find the root cause: Your team currently isn't tracking the necessary metrics to use in an ROI calculator. Your team also doesn't have enough experience with the kind of tool to build it from scratch.
• Describe your ideal outcome: Your devs add the calculator to your platform. This feature draws in new customers interested in the tool and helps current ones make the switch.
• Propose a solution: Your devs learn more about the feature’s framework and add the ability to track ROI-centric metrics. From there, you can create a project roadmap to get this feature added to the platform in a few months.

Problem statement template

Ready to start writing your own problem statement? Try our problem statement template below.

Get your team on the same page to solve problems faster

Project managers used to putting out fires can tell you how much of their job comes down to problem-solving. But before working on solutions, you need to organize your team around a clear problem statement. Find actionable, collaborative solutions by rallying everyone around a shared understanding of a problem.

Once you square away your problem statement, check out our library of over 300 templates . With FigJam, your team can plan and strategize around every step of your project. The right online whiteboard helps you exchange feedback and loop in other teams to find solutions faster.

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The Geography of Transport Systems

The spatial organization of transportation and mobility

Traffic Assignment Problem

Traffic assignment problems usually consider two dimensions.

• Generation and attraction . A place of origin generates movements that are bound (attracted) to a place of destination. The relationship between traffic generation and attraction is commonly labeled as spatial interaction. The above example considers one origin/generation and destination/attraction, but the majority of traffic assignment problems consider several origins and destinations.
• Path selection . Traffic assignment considers which paths are to be selected and the amount of traffic using these paths (if more than one unit). For simple problems, a single path will be selected, while for complex problems, several paths could be used. Factors behind the choice of traffic assignment may include cost, time, or the number of connections.

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Tabu search algorithm for solving quadratic assignment problem

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Rawaa Abdulsattar , Iraq T. Abass; Tabu search algorithm for solving quadratic assignment problem. AIP Conf. Proc. 7 May 2024; 3097 (1): 080027. https://doi.org/10.1063/5.0209862

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Although statistical solutions to Quadratic Assignment Problems (QAP) have been accessible for some time, the increasing application of Evolutionary Algorithms (EAs) to similar challenges provides a mechanism for handling QAP with extremely broad scope. The primary contribution of the study is that it normalizes all the criteria into a single scale, irrespective of their measurement units and the demand of minimum or maximum, freeing up the researchers from the burden of meticulously quantifying the quality criteria. A tabu search algorithm for quadratic assignment issues is proposed (TSQAP), which combines the constraints of tabu search with a discrete assignment problem. The effectiveness of the suggested algorithm has been compared to certain well-established approaches, and its working principle is explained with a numerical example. After repeating the solution of each issue (8) once and recording the algorithm results, it showed its agreement, once from a total (375) a repetition of the experiment while the number of times the Artificial Bee Colony (ABC) arrived (2) as for the Firefly (FA) Algorithm giving (117), also Genetic (GA) and Particle Swarm (PSO) gives (120) and the Tabu Search algorithm (136). The proposed technique (TSQAP) is shown to yield a superior solution with low computing complexity. MATLAB was used to generate all of the findings (R2020b).

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Yankees’ young infielder set to begin rehab assignment in Single-A

B ack in Spring Training, the Yankees announced that infielder Oswald Peraza needed to be shut down for 6-8 weeks with a shoulder injury. He was experiencing discomfort making throws across the diamond, and with miserable offensive and defensive numbers, it was clear that this ailment was affecting his play on the field. While the Yankees have gotten some production from Oswaldo Cabrera, they haven’t found a permanent option at third base, and one would assume that Oswald Peraza would have gotten some run there if not for his injury.

Despite being inconsistent and ineffective at the plate, Oswald Peraza’s defensive value and versatility make him a notable name on their depth chart, and he’ll begin his return to regular action with a rehab assignment in Single-A tonight.

Oswald Peraza Set to Begin Rehab Assignment as Announced by Yankees

The Tampa Tarpons will pencil in infielder Oswald Peraza as he looks to get his first game action since the injury he suffered in Spring Training. He won’t be the only Yankee down there in Tampa, with Tommy Kahnle expected to join him at the Single-A level on Wednesday when he begins his rehab assignment. Through 70 games at the Major League level, Peraza has a 75 wRC+ and .298 OBP, often struggling to recognize pitches and identify what he should or should not hit.

Some underlying metrics were enticing, as he ranked in the 73rd Percentile in SEAGER (which measures swing decisions) and the 64th Percentile in 90th Percentile Exit Velocity. Still, there are a lot of red flags here as well. He struggled to make contact in-zone and was particularly bad against breaking pitches, and the high exit velocities were rendered ineffective by a high groundball rate.

Defensively the Yankees are getting an above-average defender at three different positions, but the problem stems from how poor the offensive value is. Gleyber Torres has struggled mightily this year, but it’s not as if Oswald Peraza presents much of an upgrade over him, and he likely won’t make the team as a bench player. Instead, the Yankees would rather him get everyday at-bats in Triple-A, finding himself in a similar situation to Everson Pereira who is blocked by the myriad of outfielders ahead of him on the depth chart.

How the Yankees choose to utilize him remains to be seen, but seeing that he no longer has MiLB options after this season, it’ll be interesting to see if they give the 23-year-old infielder a chance to fight for a job at third base or not given the injury to DJ LeMahieu.

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Wisconsin's RNC delegation lands downtown hotel after first being steered to Racine

WASHINGTON – Downtown hotels will be hard to come by when the Republican National Convention kicks off in Milwaukee in just over two months.

But members of Wisconsin's convention delegation have secured their rooms.

The state's delegation will stay at the Hampton Inn & Suites just half a mile from Fiserv Forum, the epicenter of the July 15-18 convention , after many other members were originally slated to stay at a hotel in Racine, a Republican Party of Wisconsin spokesman told the Milwaukee Journal Sentinel this week.

Exactly why the delegation was moved from Racine to the downtown Milwaukee hotel was not entirely clear. But a spokeswoman for the convention on Tuesday night said the state's delegation had initially booked space in both hotels.

A March 27 email from convention officials to top Wisconsin Republicans obtained by the Journal Sentinel showed the state's delegation had 63 rooms booked at the Delta Hotel by Marriott in Racine and dozens more rooms in the Hampton Inn & Suites in downtown Milwaukee.

After the delegation "significantly reduced their hotel room needs" and dropped additional event space requests, the convention spokeswoman said, the delegation scrapped plans for Racine and shifted everyone to Milwaukee.

The delegation includes both convention delegates and Wisconsin's Republican members of Congress.

The downtown Milwaukee hotel has faced financial trouble in recent years. The Hampton Inn & Suites closed temporarily last May but reopened under new owners — the fourth operators in just over four years .

The Hampton Inn & Suites is just one of many around Milwaukee and southeastern Wisconsin the convention will put to use. Organizers have contracted with 111 hotels in Wisconsin for the RNC, officials told the Journal Sentinel .

Organizers try to keep the members of each state delegation together in a hotel or in neighboring hotels for reasons including the ease of transportation and camaraderie, but figuring out who goes where can be complicated. One factor: collaboration between the RNC and state GOP parties to boost grassroots outreach efforts.

"Who are good supporters? Who is doing good work in their states? Who are the good actors? Who is working hard? Who is meeting certain deliverables and benchmarks in their states?" Elise Dickens, the  chief executive officer for the Republican National Committee , said in March, referring to the collaborative program.

Other hotel assignments have not been publicly released.

Alison Dirr of the Milwaukee Journal Sentinel contributed to this report.

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Tigers' Gio Urshela: May begin rehab assignment this week

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Urshela (hamstring) could join Triple-A Toledo this week to begin a rehab assignment, Chris McCosky of The Detroit News reports.

Urshela remained with the Tigers for Monday's series opener in Cleveland and was spotted doing some pregame running on the field in what McCosky describes as a potential final test before the third baseman is cleared for a rehab assignment. Before landing on the 10-day injured list April 20, Urshela slashed .298/.310/.333 over 58 plate appearances with the Tigers.

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Houston Astros Infielder Shines In Injury Rehab Assignment With Sugar Land

Houston Astros infielder Grae Kessinger is getting in some at-bats with the team’s Triple-A affiliate as he prepares for a return.

• Author: Matthew Postins

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Injured Houston Astros infielder Grae Kessinger began a rehab assignment with Triple-A Sugar Land on Sunday as he edges closer to a return to the Majors.

Kessinger traveled with the Space Cowboys to their series finale with El Paso. The Space Cowboys won, 12-5.

The 26-year-old shined as the designated hitter, as he went 3-for-4 with two RBI, a walk and two runs. He hit one extra-base hit in the contest.

They were Kessinger’s first minor-league at-bats since he spent 56 games in the minor last season with Sugar Land and Double-A Corpus Christi.

The right-handed hitting outfielder experienced right shoulder discomfort after he played against Colorado on April 27. The Astros placed him on the 10-day injured list on April 30, retroactive to April 28. So he is eligible to return next week.

Before the injury he played in eight games with Houston, but he did not have a hit in 10 at-bats as he was primarily a late defensive replacement.

He made his Major League debut last season with the Astros, as he batted .200 in 26 games with one home run and one RBI.

Houston selected the Oxford, Miss., native in the second round of the 2019 MLB Draft out of Ole Miss. He is the nephew of Keith Kessinger and the grandson of Don Kessinger, both of whom played in the Majors.

The Astros are lacking in outfield depth as well, as Chas McCormick is on the 15-day injured list with discomfort in his right hamstring. He’s recently begun a running program in an effort to prepare for a rehab assignment in the minors.

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