Hybrid algorithm based on Chemical Reaction Optimization and Lin-Kernighan local search for the Traveling Salesman Problem

Jian Sun, Yuting Wang, Jun-qing Li, K. Gao
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引用次数: 19

Abstract

Chemical Reaction Optimization (CRO) is a new heuristic optimization method mimicking the process of a chemical reaction where molecules interact with each other aiming to reach the minimum state of free energy. CRO has demonstrated its capability in solving NP-hard optimization problems. The Lin-Kernighan(LK) local search is known to be one of the most successful heuristics for the Traveling Salesman Problem (TSP). In this paper, we present a hybrid algorithm based on CRO and LK local search for TSP. The proposed algorithm consider the tradeoff between the exploration abilities of CRO and the exploitation abilities of LK local searcher. Experimental results show that the proposed algorithm is efficient.
基于化学反应优化和Lin-Kernighan局部搜索的旅行商问题混合算法
化学反应优化(CRO)是一种新的启发式优化方法,它模拟了分子间相互作用的化学反应过程,以达到最小的自由能状态为目标。CRO在求解NP-hard优化问题上已经证明了它的能力。Lin-Kernighan(LK)局部搜索是求解旅行推销员问题(TSP)最成功的启发式方法之一。本文提出了一种基于CRO和LK局部搜索的TSP混合算法。该算法考虑了CRO的搜索能力和LK局部搜索器的开发能力之间的权衡。实验结果表明,该算法是有效的。
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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