Multiple Optimal Solutions: Assignment Problem

Sometimes, it is possible to cross out all the zeros in the reduced matrix in two or more ways.

If you can choose a zero cell arbitrarily, then there will be multiple optimal solutions with the same total pay-off for assignments made. In such a case, the management may select that set of optimal assignments, which is more suited to their requirement.

  • Maximization Problem
  • Unbalanced Assignment Problem

Example: Multiple Optimal Solutions

Consider the following assignment problem : The Spicy Spoon restaurant has four payment counters. There are four persons available for service. The cost of assigning each person to each counter is given in the following table.

Assign one person to one counter to minimize the total cost.

After applying steps 1 to 3 of the Hungarian Method, we obtain the following matrix.

Use Horizontal Scrollbar to View Full Table Calculation.

Now by applying the usual procedure, we get the following matrix.

The resulting matrix suggest the alternative optimal solutions as shown in the following tables.

The persons B & C may be assigned either to job 2 or 3. The two alternative assignments are:

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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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Assignment Problem: Meaning, Methods and Variations | Operations Research

the assignment problem will have alternate solutions

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:

the assignment problem will have alternate solutions

International Symposium on Combinatorial Optimization

ISCO 2022: Combinatorial Optimization pp 172–186 Cite as

Nash Balanced Assignment Problem

  • Minh Hieu Nguyen 11 ,
  • Mourad Baiou 11 &
  • Viet Hung Nguyen 11  
  • Conference paper
  • First Online: 21 November 2022

312 Accesses

1 Citations

Part of the Lecture Notes in Computer Science book series (LNCS,volume 13526)

In this paper, we consider a variant of the classic Assignment Problem (AP), called the Balanced Assignment Problem (BAP) [ 2 ]. The BAP seeks to find an assignment solution which has the smallest value of max-min distance : the difference between the maximum assignment cost and the minimum one. However, by minimizing only the max-min distance, the total cost of the BAP solution is neglected and it may lead to an inefficient solution in terms of total cost. Hence, we propose a fair way based on Nash equilibrium [ 1 , 3 , 4 ] to inject the total cost into the objective function of the BAP for finding assignment solutions having a better trade-off between the two objectives: the first aims at minimizing the total cost and the second aims at minimizing the max-min distance. For this purpose, we introduce the concept of Nash Fairness (NF) solutions based on the definition of proportional-fair scheduling adapted in the context of the AP: a transfer of utilities between the total cost and the max-min distance is considered to be fair if the percentage increase in the total cost is smaller than the percentage decrease in the max-min distance and vice versa.

We first show the existence of a NF solution for the AP which is exactly the optimal solution minimizing the product of the total cost and the max-min distance. However, finding such a solution may be difficult as it requires to minimize a concave function. The main result of this paper is to show that finding all NF solutions can be done in polynomial time. For that, we propose a Newton-based iterative algorithm converging to NF solutions in polynomial time. It consists in optimizing a sequence of linear combinations of the two objective based on Weighted Sum Method [ 5 ]. Computational results on various instances of the AP are presented and commented.

  • Combinatorial optimization
  • Balanced assignment problem
  • Proportional fairness
  • Proportional-fair scheduling
  • Weighted sum method

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Minh Hieu Nguyen, Mourad Baiou & Viet Hung Nguyen

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ESSEC Business School of Paris, Cergy Pontoise Cedex, France

Ivana Ljubić

IBM TJ Watson Research Center, Yorktown Heights, NY, USA

Francisco Barahona

Georgia Institute of Technology, Atlanta, GA, USA

Santanu S. Dey

Université Paris-Dauphine, Paris, France

A. Ridha Mahjoub

Proposition 1 . There may be more than one NF solution for the AP.

Let us illustrate this by an instance of the AP having the following cost matrix

By verifying all feasible assignment solutions in this instance, we obtain easily three assignment solutions \((1-1, 2-2, 3-3), (1-2, 2-3, 3-1)\) , \((1-3, 2-2, 3-1)\) and \((1-3, 2-1, 3-2)\) corresponding to 4 NF solutions (280, 36), (320, 32), (340, 30) and (364, 28). Note that \(i-j\) where \(1 \le i,j \le 3\) represents the assignment between worker i and job j in the solution of this instance.     \(\square \)

We recall below the proofs of some recent results that we have published in [ 10 ]. They are needed to prove the new results presented in this paper.

Theorem 2 [ 10 ] . \((P^{*},Q^{*}) = {{\,\mathrm{arg\,min}\,}}_{(P,Q) \in \mathcal {S}} PQ\) is a NF solution.

Obviously, there always exists a solution \((P^{*},Q^{*}) \in \mathcal {S}\) such that

Now \(\forall (P',Q') \in \mathcal {S}\) we have \(P'Q' \ge P^{*}Q^{*}\) . Then

The first inequality holds by the Cauchy-Schwarz inequality.

Hence, \((P^{*},Q^{*})\) is a NF solution.     \(\square \)

Theorem 3 [ 10 ] . \((P^{*},Q^{*}) \in \mathcal {S}\) is a NF solution if and only if \((P^{*},Q^{*})\) is an optimal solution of \(\mathcal {P(\alpha ^{*})}\) where \(\alpha ^{*} = \frac{Q^{*}}{P^{*}}\) .

Firstly, let \((P^{*},Q^{*})\) be a NF solution and \(\alpha ^{*} = \frac{Q^{*}}{P^{*}}\) . We will show that \((P^{*},Q^{*})\) is an optimal solution of \(\mathcal {P(\alpha ^{*})}\) .

Since \((P^{*},Q^{*})\) is a NF solution, we have

Since \(\alpha ^{*} = \frac{Q^{*}}{P^{*}}\) , we have \(\alpha ^{*}P^{*}+Q^{*} = 2Q^{*}\) .

Dividing two sides of ( 6 ) by \(P^{*} > 0\) we obtain

So we deduce from ( 7 )

Hence, \((P^{*},Q^{*})\) is an optimal solution of \(\mathcal {P}(\alpha ^{*})\) .

Now suppose \(\alpha ^{*} = \frac{Q^{*}}{P^{*}}\) and \((P^{*},Q^{*})\) is an optimal solution of \(\mathcal {P}(\alpha ^{*})\) , we show that \((P^{*},Q^{*})\) is a NF solution.

If \((P^{*},Q^{*})\) is not a NF solution, there exists a solution \((P',Q') \in \mathcal {S}\) such that

We have then

which contradicts the optimality of \((P^{*},Q^{*})\) .     \(\square \)

Lemma 3 [ 10 ] . Let \(\alpha , \alpha ' \in \mathbb {R}_+\) and \((P_{\alpha }, Q_{\alpha })\) , \((P_{\alpha '}, Q_{\alpha '})\) be the optimal solutions of \(\mathcal {P(\alpha )}\) and \(\mathcal {P(\alpha ')}\) respectively, if \(\alpha \le \alpha '\) then \(P_{\alpha } \ge P_{\alpha '}\) and \(Q_{\alpha } \le Q_{\alpha '}\) .

The optimality of \((P_{\alpha }, Q_{\alpha })\) and \((P_{\alpha '}, Q_{\alpha '})\) gives

By adding both sides of ( 8a ) and ( 8b ), we obtain \((\alpha - \alpha ') (P_{\alpha } - P_{\alpha '}) \le 0\) . Since \(\alpha \le \alpha '\) , it follows that \(P_{\alpha } \ge P_{\alpha '}\) .

On the other hand, inequality ( 8a ) implies \(Q_{\alpha '} - Q_{\alpha } \ge \alpha (P_{\alpha } - P_{\alpha '}) \ge 0\) that leads to \(Q_{\alpha } \le Q_{\alpha '}\) .     \(\square \)

Lemma 4 [ 10 ] . During the execution of Procedure Find ( \(\alpha _{0})\) in Algorithm 1 , \(\alpha _{i} \in [0,1], \, \forall i \ge 1\) . Moreover, if \(T_{0} \ge 0\) then the sequence \(\{\alpha _i\}\) is non-increasing and \(T_{i} \ge 0, \, \forall i \ge 0\) . Otherwise, if \(T_{0} \le 0\) then the sequence \(\{\alpha _i\}\) is non-decreasing and \(T_{i} \le 0, \, \forall i \ge 0\) .

Since \(P \ge Q \ge 0, \, \forall (P, Q) \in \mathcal {S}\) , it follows that \(\alpha _{i+1} = \frac{Q_i}{P_i} \in [0,1], \, \forall i \ge 0\) .

We first consider \(T_{0} \ge 0\) . We proof \(\alpha _i \ge \alpha _{i+1}, \, \forall i \ge 0\) by induction on i . For \(i = 0\) , we have \(T_{0} = \alpha _{0} P_{0} - Q_{0} = P_{0}(\alpha _{0}-\alpha _{1}) \ge 0\) , it follows that \(\alpha _{0} \ge \alpha _{1}\) . Suppose that our hypothesis is true until \(i = k \ge 0\) , we will prove that it is also true with \(i = k+1\) .

Indeed, we have

The inductive hypothesis gives \(\alpha _k \ge \alpha _{k+1}\) that implies \(P_{k+1} \ge P_k > 0\) and \(Q_{k} \ge Q_{k+1} \ge 0\) according to Lemma 3 . It leads to \(Q_{k}P_{k+1} - P_{k}Q_{k+1} \ge 0\) and then \(\alpha _{k+1} - \alpha _{k+2} \ge 0\) .

Hence, we have \(\alpha _{i} \ge \alpha _{i+1}, \, \forall i \ge 0\) .

Consequently, \(T_{i} = \alpha _{i}P_{i} - Q_{i} = P_{i}(\alpha _{i}-\alpha _{i+1}) \ge 0, \, \forall i \ge 0\) .

Similarly, if \(T_{0} \le 0\) we obtain that the sequence \(\{\alpha _i\}\) is non-decreasing and \(T_{i} \le 0, \, \forall i \ge 0\) . That concludes the proof.     \(\square \)

Lemma 5 [ 10 ] . From each \(\alpha _{0} \in [0,1]\) , Procedure Find \((\alpha _{0})\) converges to a coefficient \(\alpha _{k} \in \mathcal {C}_{0}\) satisfying \(\alpha _{k}\) is the unique element \(\in \mathcal {C}_{0}\) between \(\alpha _{0}\) and \(\alpha _{k}\) .

As a consequence of Lemma 4 , Procedure \(\textit{Find}(\alpha _{0})\) converges to a coefficient \(\alpha _{k} \in [0,1], \forall \alpha _{0} \in [0,1]\) .

By the stopping criteria of Procedure Find \((\alpha _{0})\) , when \(T_{k} = \alpha _{k} P_{k} - Q_{k} = 0\) we obtain \(\alpha _{k} \in C_{0}\) and \((P_{k},Q_{k})\) is a NF solution. (Theorem 3 )

If \(T_{0} = 0\) then obviously \(\alpha _{k} = \alpha _{0}\) . We consider \(T_{0} > 0\) and the sequence \(\{\alpha _i\}\) is now non-negative, non-increasing. We will show that \([\alpha _{k},\alpha _{0}] \cap \mathcal {C}_{0} = \alpha _{k}\) .

Suppose that we have \(\alpha \in (\alpha _{k},\alpha _{0}]\) and \(\alpha \in \mathcal {C}_{0}\) corresponding to a NF solution ( P ,  Q ). Then there exists \(1 \le i \le k\) such that \(\alpha \in (\alpha _{i}, \alpha _{i-1}]\) . Since \(\alpha \le \alpha _{i-1}\) , \(P \ge P_{i-1}\) and \(Q \le Q_{i-1}\) due to Lemma 3 . Thus, we get

By the definitions of \(\alpha \) and \(\alpha _{i}\) , inequality ( 9 ) is equivalent to \(\alpha \le \alpha _{i}\) which leads to a contradiction.

By repeating the same argument for \(T_{0} < 0\) , we also have a contradiction.     \(\square \)

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Nguyen, M.H., Baiou, M., Nguyen, V.H. (2022). Nash Balanced Assignment Problem. In: Ljubić, I., Barahona, F., Dey, S.S., Mahjoub, A.R. (eds) Combinatorial Optimization. ISCO 2022. Lecture Notes in Computer Science, vol 13526. Springer, Cham. https://doi.org/10.1007/978-3-031-18530-4_13

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COMMENTS

  1. Solved The total opportunity cost matrix is obtained by

    The assignment problem will have alternate solutions (a) when total opportunity cost matrix has at least one zero in each row and column, (b) When all rows have two zeros, (c) When there is a tie between zero opportunity cost cells, (d) If two diagonal elements are zeros. ... The problem will get alternate solutions, (c) The problem degenerates ...

  2. Alternative Solution to Assignment problem & Solved Examples

    This lecture explains how to find an alternative solution to assignment problems.Other videos @DrHarishGarg Assignment Problem - Mathematical Models: Link: h...

  3. The assignment problem will have alternate solutions

    14) An optimal solution of an assignment problem can be obtained only if. a. Each row and column has only one zero element b. Each row and column has at least one zero element c. The data are arrangement in a square matrix d. None of the above. d. None of the above. 15) Flood's technique of solving an assignment matrix uses the concept of.

  4. Operations Research Multiple choice Questions and Answers. Page 8

    The assignment problem will have alternate solutions when the total opportunity cost matrix has _____ atleast one zero in each row and column; when all rows have two zeros; when there is a tie between zero opportunity cost cells; if two diagonal elements are zeros. View answer

  5. Operations Research BY Murthy MCQ with Answer

    The assignment problem will have alternate solutions ( a) when total opportunity cost matrix has at least one zero in each row and column, ( b) When all rows have two zeros, ( c) When there is a tie between zero opportunity cost cells, ( d) If two diagonal elements are zeros.

  6. Transportation and assignment MCQs

    The assignment problem will have alternate solutions when _____ (a) at least one zero in each row and column (b) when all rows have two zeros (c) when there is a tie between zero opportunity cost cells (d) if two diagonal elements are zeros. ... The assignment problem will have alternate solutions when _____ (a) at least one zero in each row ...

  7. Multiple Optimal Solutions, Assignment Problem

    Example: Multiple Optimal Solutions. Consider the following assignment problem: The Spicy Spoon restaurant has four payment counters. There are four persons available for service. The cost of assigning each person to each counter is given in the following table. Assign one person to one counter to minimize the total cost.

  8. How to Solve the Assignment Problem: A Complete Guide

    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.

  9. Assignment problem

    The assignment problem is a fundamental combinatorial optimization problem. In its most general form, the problem is as follows: The problem instance has a number of agents and a number of tasks. Any agent can be assigned to perform any task, incurring some cost that may vary depending on the agent-task assignment.

  10. Computing k different solutions to the assignment problem

    Highlights • We consider the linear assignment problem and the semi-assignment. • We want to find several alternative solutions to the problem. • The associated cost has to be minimized. • We prese...

  11. Computing k different solutions to the assignment problem

    Abstract. Assignment problems are about the best way of matching the elements of a first set with the elements of a second set. In Semi-Assignment problems, more than one element of the first set can be assigned to each element of the second. In many situations, a solution to the same Assignment or Semi-Assignment problem has to be implemented ...

  12. Computing k different solutions to the assignment problem

    It is straightforward to transform a semiassignment to an assignment problem by duplicating each element j of the second set to identical elements, , and by setting . As an alternative, the semiassignment problem can be tackled as a problem stand-alone (see, e.g., Kennington & Wang (1992)). In many situations, the solution to the same ...

  13. Semester 1 Notes 19

    The assignment problem will have alternate solutions when total opportunity cost matrix has (a) At least one zero in each row and column, (b) When all rows have two zeros, (c) When there is a tie between zero opportunity cost cells, (d) If two diagonal elements are zeros.

  14. Assignment Problem: Meaning, Methods and Variations

    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 ...

  15. Developing Alternative Solutions

    Developing Alternative Solutions. Aug 3. Written By Jeff Kern. As an established working professional enrolled in college classes, I appreciate the real-world applicability and usefulness of my assigned coursework. One such assignment was Developing Alternative Solutions from my Team Building and Problem Solving course in April 2020, where I ...

  16. PDF The Assignment Problem and Primal-Dual Algorithms 1 Assignment Problem

    The Assignment Problem and Primal-Dual Algorithms 1 Assignment Problem Suppose we want to solve the following problem: We are given a set of people I, and a set of jobs J, with jIj= jJj= n ... solution to the LP, so the optimal value of the LP must be at most the optimal value of the assignment problem. We consider the dual of the LP: max X i2I ...

  17. FBA MCQ Flashcards

    C. 3. In Index method of solving assignment problem (a) The whole matrix is divided by smallest element (b) The smallest element is subtracted from whole matrix (c) Each row or column is divided by smallest element in that particular row or column (d) The whole matrix is multiplied by - 1.

  18. Assignment problem or something else?

    The assignment problem is a good fit except, as I understand it, the solutions all value giving as many agents as possible their #1 choice, or finding the "lowest cost" solution. So solutions to the assignment problem would find Scenario A above to be the better solution. In my scenario, the best solution may not include anyone getting their ...

  19. Alternative solution on an assigment problem using PuLP

    solve original assignment problem. set k := 0. store solution in a [i,j,k] solve problem with additional constraint. if infeasible: STOP. if no more solutions needed: STOP. k := k + 1. go to step 3. An alternative would be to use a solver that has a so-called solution pool.

  20. The assignment problem will have alternate solutions when the total

    The assignment problem will have alternate solutions when the total opportunity cost matrix has _____ A:atleast one zero in each row and column, B:when all rows have two zeros H E L P D I C E ... The assignment problem is a special case of transportation problem in which _____.

  21. PDF 17 The Assignment Problem

    Then X∗ solves the assignment problem specified by C since z(X∗)=0and z(X) ≥ 0 for any other solution X.ByExample5,X∗ is also an optimal solution to the assignment problem specified by C.NotethatX∗ corresponds to the permutation 132. The method used to obtain an optimal solution to the assignment problem specified by C

  22. Nash Balanced Assignment Problem

    The Balanced Assignment Problem (BAP) is a variant of the classic AP where instead of minimizing the total cost, we minimize the max-min distance which is the difference between the maximum assignment cost and the minimum one in the assignment solution. In [ 2 ], the authors proposed an efficient threshold-based algorithm to solve the BAP in ...

  23. Operations Research Multiple choice Questions and Answers. Page 4

    The assignment problem is always a _____matrix. circle; square; rectangle; triangle; View answer. ... alternate optimum solution. View answer. ... alternate optimum solution. 40. Mathematical model of linear programming problem is important because _____. it helps in converting the verbal description and numerical data into mathematical ...