Enhanced Artificial Bee Colony Algorithm with SPV for Travelling Salesman Problem

Ashay Shrivastava, Manish Gupta, Shashank Swami
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引用次数: 4

Abstract

Artificial Bee Colony (ABC) Algorithm is an optimization algorithm used to find out the global optima. In ABC, each bee stores the information of feasible solution or candidate solution and stochastically modifies this over time, based on the information provided by neighboring bees, it speculative modifies over time and based on the best solution found by the bee itself.. In this proposed work, enhanced ABC algorithm with SPV for travelling salesman problem is used. In this modified bee colony algorithm, additional phase in the form of mutation is used and SPV rule is used in this work for improving local search. After modification, proposed algorithm is implemented on standard travelling salesman problem for checking the efficiency of proposed work. The experimental results are compared with ABC algorithm and ABC with SPV algorithm.
旅行商问题的改进SPV人工蜂群算法
人工蜂群(Artificial Bee Colony, ABC)算法是一种寻找全局最优解的优化算法。在ABC中,每只蜜蜂存储可行方案或候选方案的信息,并根据邻近蜜蜂提供的信息随时间随机修改,它根据自己发现的最佳方案随时间推测修改。本文采用带SPV的增强型ABC算法求解旅行商问题。在改进的蜂群算法中,采用了突变形式的附加阶段,并采用了SPV规则来改进局部搜索。修改后,将该算法应用于标准旅行商问题,检验算法的有效性。实验结果与ABC算法和ABC带SPV算法进行了比较。
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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