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An improved ACO algorithm for the bin packing problem with conflicts based on graph coloring model

机译:基于图着色模型的带冲突的装箱问题的改进ACO算法

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Bin packing problem with conflicts(BPPC) is a complex combinatorial optimization problem originated from logistics, whose objective is packing all the items with the least number of bins and satisfying the conflict constraints among the items. In this paper, we firstly give the description and 0–1 integer programming model of BPPC, and then transform the model into the representation of conflict graph structure. After that, an ant colony optimization(ACO) algorithm framework is proposed for solving the conflict elimination procedure of BPPC based on a graph coloring heuristic, according to the results of conflict elimination, an improved first-fit decreasing algorithm is used to finish the packing operations of the subsets of items without conflicts. The experiments show that the improve ACO algorithm in this paper is valid and could provide a feasible and high-quality solutions of BPPC efficiently.
机译:带有冲突的装箱问题(BPPC)是一个复杂的组合优化问题,起源于物流,其目标是包装所有装箱数最少的物品并满足物品之间的冲突约束。在本文中,我们首先给出了BPPC的描述和0-1整数规划模型,然后将其转换为冲突图结构的表示形式。在此基础上,提出了一种基于图着色启发式的蚁群优化算法框架来解决BPPC的冲突消除过程,根据冲突消除的结果,采用改进的首次拟合递减算法完成打包。项目子集的操作无冲突。实验表明,本文提出的改进的ACO算法是有效的,可以有效地提供一种可行且高质量的BPPC解决方案。

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