TY - JOUR ID - 1697 TI - Solving Traveling Salesman Problem based on Biogeography-based Optimization and Edge Assembly Cross-over JO - Journal of AI and Data Mining JA - JADM LA - en SN - 2322-5211 AU - Salehi, A. AU - Masoumi, B. AD - Faculty of Computer and information Technology, Islamic Azad University, Qazvin Branch, Qazvin, Iran. Y1 - 2020 PY - 2020 VL - 8 IS - 3 SP - 313 EP - 329 KW - Biogeography-Based Optimization KW - Evolutionary Algorithms KW - Traveling Salesman Problem DO - 10.22044/jadm.2020.7835.1922 N2 - Biogeography-Based Optimization (BBO) algorithm has recently been of great interest to researchers for simplicity of implementation, efficiency, and the low number of parameters. The BBO Algorithm in optimization problems is one of the new algorithms which have been developed based on the biogeography concept. This algorithm uses the idea of animal migration to find suitable habitats for solving optimization problems. The BBO algorithm has three principal operators called migration, mutation and elite selection. The migration operator plays a very important role in sharing information among the candidate habitats. The original BBO algorithm, due to its poor exploration and exploitation, sometimes does not perform desirable results. On the other hand, the Edge Assembly Crossover (EAX) has been one of the high power crossovers for acquiring offspring and it increased the diversity of the population. The combination of biogeography-based optimization algorithm and EAX can provide high efficiency in solving optimization problems, including the traveling salesman problem (TSP). This paper proposed a combination of those approaches to solve traveling salesman problem. The new hybrid approach was examined with standard datasets for TSP in TSPLIB. In the experiments, the performance of the proposed approach was better than the original BBO and four others widely used metaheuristics algorithms. UR - https://jad.shahroodut.ac.ir/article_1697.html L1 - https://jad.shahroodut.ac.ir/article_1697_98c0bddece1cb575e0cb9c519d6fa4ec.pdf ER -