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首页> 外文期刊>INFORMS journal on computing >A Logarithmic Method for Reducing Binary Variables and Inequality Constraints in Solving Task Assignment Problems
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A Logarithmic Method for Reducing Binary Variables and Inequality Constraints in Solving Task Assignment Problems

机译:减少任务分配问题中的二元变量和不等式约束的对数方法

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摘要

This paper studies the classical task assignment problem (TAP) in which M unbreakable tasks are assigned to N agents with the objective to minimize the communication and process costs subject to each agent's capacity constraint. Because a large-size TAP involves many binary variables, most, if not all, traditional methods experience the difficulty in solving the problem within a reasonable time period. Recent works present a logarithmic approach to reduce the number of binary variables in problems with mixed-integer variables. This study proposes a new logarithmic method that significantly reduces the numbers of binary variables and inequality constraints in solving task assignment problems. Our numerical experiments demonstrate that the proposed method is superior to other known methods of this kind for solving large-size TAPs.
机译:本文研究经典任务分配问题(TAP),其中将M个牢不可破的任务分配给N个代理,目的是在每个代理的能力约束下将通信和流程成本降至最低。由于大型TAP涉及许多二进制变量,因此大多数(即使不是全部)传统方法也难以在合理的时间内解决问题。最近的工作提出了一种对数方法来减少混合整数变量问题中的二进制变量数量。这项研究提出了一种新的对数方法,该方法可以极大地减少解决任务分配问题中的二进制变量和不等式约束的数量。我们的数值实验表明,所提出的方法在解决大型TAP方面优于其他此类已知方法。

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