A Parallel Large Neighborhood Search-Based Heuristic for the Disjunctively Constrained Knapsack Problem

M. Hifi, S. Nègre, T. Saadi, Sagvan Saleh, Lei Wu
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引用次数: 11

Abstract

This paper proposes a parallel large neighborhood search-based heuristic for solving the Disjunctively Constrained Knapsack Problem (DCKP), which has an important impact on the transportation issues. The proposed approach is designed using Message Passing Interface (MPI). The effectiveness of MPI's allows us to build a flexible message passing model of parallel programming. Meanwhile, large neighborhood search heuristic is introduced in the model in order to propose an efficient resolution method yielding high quality solutions. The results provided by the proposed method are compared to those reached by the Cplex solver and to those obtained by one of the best methods of the literature. As shown from the experimental results, the proposed model is able to provide high quality solutions with fast runtime on most cases of the benchmark literature.
解离约束背包问题的并行大邻域搜索启发式算法
本文提出一种基于并行大邻域搜索的启发式算法,用于解离约束背包问题(DCKP),该问题对交通问题具有重要影响。该方法采用消息传递接口(Message Passing Interface, MPI)设计。MPI的有效性使我们能够建立一个灵活的并行编程消息传递模型。同时,在模型中引入大邻域搜索启发式算法,提出一种高效的求解方法。将所提出的方法与复杂解算器所得到的结果以及文献中最好的一种方法所得到的结果进行了比较。实验结果表明,在大多数基准文献的情况下,所提出的模型能够提供高质量和快速运行的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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