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Solving the Many to Many assignment problem by improving the Kuhn-Munkres algorithm with backtracking

机译:通过回溯改进Kuhn-Munkres算法来解决多对多分配问题

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The Many to Many (M-M) assignment problem is an important open problem where one task is assigned to many, but different, agents and one agent may undertake many, but different, tasks. The Kuhn-Munkres (K-M) algorithm is a famous and traditional process used in dealing with assignment problems. In this paper, we propose a solution to the M-M assignment problem by improving the K-M algorithm with backtracking (KMB). To demonstrate the solution's suitability, we prove that the proposed KMB algorithm is valid and that the worst time complexity of the KMB algorithm is O ((Sigma L-a[i])(3)), where L-a[i] denotes the maximum number of tasks that can be assigned to agent i. After that, we discuss several critical problems related to the algorithm and provide the necessary and sufficient conditions of solving the M-M assignment problem. Finally, we demonstrate, through experimentation, the validity, practicality and efficiency of the KMB algorithm. (C) 2016 Elsevier B.V. All rights reserved.
机译:多对多(M-M)分配问题是一个重要的开放问题,其中一个任务分配给许多但不同的代理,而一个代理可以承担许多但不同的任务。 Kuhn-Munkres(K-M)算法是用于处理分配问题的著名且传统的过程。在本文中,我们通过改进带回溯的K-M算法(KMB)提出了M-M分配问题的解决方案。为了证明该解决方案的适用性,我们证明了所提出的KMB算法是有效的,并且KMB算法的最差时间复杂度为O((Sigma La [i])(3)),其中La [i]表示最大数目。可以分配给代理i的任务。之后,我们讨论了与算法有关的几个关键问题,并提供了解决M-M分配问题的必要和充分条件。最后,我们通过实验证明了KMB算法的有效性,实用性和有效性。 (C)2016 Elsevier B.V.保留所有权利。

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