计算机工程与应用2024，Vol.60Issue(1)：145-153,9.DOI:10.3778/j.issn.1002-8331.2303-0012
求解TSP的离散野马优化算法
Discrete Wild Horse Optimizer for TSP
摘要
Abstract
A new metaheuristic algorithm called discrete wild horse optimizer(DWHO)is proposed for solving the traveling salesman problem.The minimum position matching value method(MPMV)is applied to discretize and decode the obtained solutions.To improve the algorithm's search capability,a variable neighborhood search strategy is introduced to enhance its local search capability and accelerate the convergence speed by combining wild horse grazing behavior,mating behavior,exchange and selection of leaders.33 benchmark examples from the standard library TSPLIB are selected for experimentation,and it is compared with two other algorithms,artificial bee colony algorithm with sequence exchange(ABCSS),discrete spider monkey optimization(DSMO).The experimental results indicate that the maximum improve-ment rates of the optimal solutions of DWHO,compared with ABCSS,and DSMO algorithms,are 4.52%and 3.41%,respectively.Moreover,the convergence speed of the discrete horse optimizer in solving TSP is significantly better than the above two algorithms.The results also indicate that the discrete horse optimizer has advantages in terms of solving ability and accuracy.关键词
离散野马优化算法/旅行商问题/最小位置匹配值法/最优解改进率Key words
discrete wild horse optimizer(DWHO)/traveling salesman problem(TSP)/min-position matched value(MPMV)/best solution improvement rate分类
信息技术与安全科学引用本文复制引用
蔡延光,方春城,吴艳林,陈华君..求解TSP的离散野马优化算法[J].计算机工程与应用,2024,60(1):145-153,9.基金项目
国家自然科学基金(61074147,61901304) （61074147,61901304）
广东省科技计划项目(2016A050502060,2020B1010010005) （2016A050502060,2020B1010010005）
广东省教育厅特色创新类科研项目(2022KTSCX358) （2022KTSCX358）
广东省教育科学规划课题(2021GXJK739) （2021GXJK739）
广州市科技计划项目(202206010011,2023B03J1339) （202206010011,2023B03J1339）
揭阳职业技术学院科研项目(2022JYCKY02). （2022JYCKY02）
