This paper presents a comparative performance analysis of some metaheuristics such as the African Buffalo Optimization algorithm (ABO), Improved Extremal Optimization (IEO), Model-Induced Max-Min Ant Colony Optimization (MIMM-ACO), Max-Min Ant System (MMAS), Cooperative Genetic Ant System (CGAS), and the heuristic, Randomized Insertion Algorithm (RAI) to solve the asymmetric Travelling Salesman Problem (ATSP). Quite unlike the symmetric Travelling Salesman Problem, there is a paucity of research studies on the asymmetric counterpart. This is quite disturbing because most real-life applications are actually asymmetric in nature. These six algorithms were chosen for their performance comparison because they have posted some of the best results in literature and they employ different search schemes in attempting solutions to the ATSP. The comparative algorithms in this study employ different techniques in their search for solutions to ATSP: the African Buffalo Optimization employs the modified Karp–Steele mechanism, Model-Induced Max-Min Ant Colony Optimization (MIMM-ACO) employs the path construction with patching technique, Cooperative Genetic Ant System uses natural selection and ordering; Randomized Insertion Algorithm uses the random insertion approach, and the Improved Extremal Optimization uses the grid search strategy. After a number of experiments on the popular but difficult 15 out of the 19 ATSP instances in TSPLIB, the results show that the African Buffalo Optimization algorithm slightly outperformed the other algorithms in obtaining the optimal results and at a much faster speed.

中文翻译：

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计算智能技术解决非对称旅行商问题的比较性能分析

本文介绍了一些元启发式方法的比较性能分析，例如非洲水牛优化算法（ABO），改进的极值优化（IEO），模型诱导的最大-最小蚁群优化（MIMM-ACO），最大-最小蚁群系统（MMAS） ），合作遗传蚂蚁系统（CGAS）和启发式随机插入算法（RAI）来解决非对称旅行商问题（ATSP）。与对称旅行商问题完全不同，对非对称交易者的研究很少。这非常令人不安，因为大多数现实生活中的应用程序实际上实际上都是非对称的。选择这6种算法进行性能比较是因为它们在文献中已经发布了一些最佳结果，并且它们在尝试解决ATSP问题时采用了不同的搜索方案。本研究中的比较算法在寻找ATSP解决方案时采用了不同的技术：非洲水牛城优化采用改进的Karp-Steele机制，模型诱导的最大-最小蚁群优化（MIMM-ACO）采用带有修补技术的路径构造，合作遗传蚂蚁系统采用自然选择和排序；随机插入算法使用随机插入方法，而改进的极值优化使用网格搜索策略。在TSPLIB的19个ATSP实例中，对流行但困难的15个实例进行了许多实验后，结果表明，非洲水牛优化算法在获得最佳结果方面并以更快的速度略胜于其他算法。