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> DOI:10.16366/j.cnki.1000-2367.2024.12.12.0004

基于深度搜索的改进角蜥蜴优化算法求解 TSP问题

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摘要:

针对角蜥蜴优化算法(homedlizard optmization algorithm,HLOA)无法求解旅行商问题(travelngsalesman problem,TSP),并且改进的连续型元启发式算法求解TSP问题存在寻优能力不足等问题,提出一种基于深度搜索的改进角蜥蜴优化算法(improved horned lizard optimization algorithm with depth search.DSIHLOA).该算法通过双重编码方式将HLOA离散化;通过提出的信息共享策略提高算法前期的收敛速度;设计深度搜索过程提高算法的搜索能力,并提出Greedy-Insert、Greedy-Swap和2-Opt-2算子应用到深度搜索过程中.通过多个TSP标准算例对 DSIHLOA的性能进行测试,并与传统元启发式算法对比.结果表明:DSIHLOA拥有较好的求解精度和收敛速度;与其他文献的改进连续型元启发式算法进行对比,DSIHLOA具有较好的寻优能力和稳定性。

Aiming at the problems of the homed lizard optimization algorithm (HLOA) cannot solve the discrete problems, for example, the traveling salesman problem (TSP), and the improved continuous metaheuristic algorithm has insuffi-cient optimization capability for solving the TSP, this paper proposed an improved horned lizard optimization algorithm with depth search(DSIHLOA). The algorithm discretizes the HLOA utilizing double coding. The proposed information sharing strategy improves the convergence speed of the algorithm at the early stage. The depth search process improves the search ability of the algorithm. The proposed Greedy-Insert, Greedy-Swap, and 2-Opt-2 operators are applied to the depth search process.Through simulation experiments on several TSP instances and comparing them with traditional metaheuristic algorithms, the results show that DSIHLOA possesses better solution accuracy and convergence speed. Compared with other improved continuous metaheuristic algorithms in the literature, the results show that DSIHLOA possesses better optimization search ability and stability.

作者:

魏杰,习毅聪,赵璇

WeiJie,Xi Yicong,Zhao Xuan

机构地区:

华中科技大学管理学院;国家电网有限公司国网北京市电力公司物资分公司

引用本文:

魏杰,习毅聪,赵璇。基于深度搜索的改进角蜥蜴优化算法求解TSP问题[J].河南师范大学学报(自然科学版),2026.54(1):83-91.(Wei Jie,Xi Yicong, Zhao Xuan.Improved horned lizard optimization algorithm with depth search for solving traveling salesman problem [J]. Journal of Henan Normal University (Natural Science Edition),2026,54(1):83-91.DOI:10.16366/j.cnki.1000-2367.2024.12.12.0004.)

基金:

国家电网有限公司科技项目

关键词:

旅行商问题;角蜥蜴优化算法;信息共享策略;深度搜索

traveling salesman problem; horned lizard optimization algorithm; information sharing strategy; depthsearch

分类号:

TP18


基于深度搜索的改进角蜥蜴优化算法求解 TSP问题.pdf


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