摘要
作为一种新兴的群智能启发式算法,蝙蝠算法近年来被广泛用于求解离散、连续、及组合优化问题。针对典型组合优化问题中的旅行商问题,提出了一种基于偏序对改进的蝙蝠算法用于求解离散型旅行商问题。通过对蝙蝠速度、位置的更新,使算法具有更强的适用性。对16个标准旅行商问题(traveling salesman problem,TSP)进行测试与对比分析以验证算法有效性。实验结果表明:所提出的偏序对蝙蝠算法在大多数实例中均优于其他算法。
As a novel heuristic algorithm for swarm intelligence,the bat algorithm has been widely used in recent years to solve discrete,continuous,and combinatorial optimization problems.The traveling salesman problem(TSP)is one of typical combinatorial optimization problems.Therefore,an improved bat algorithm based on partial order pair was proposed for solving discrete traveling salesman problems.By updating the bat speed and position,stronger applicability was achieved by the proposed algorithm.16 standard TSP problems were applied to verify the feasibility and effectiveness of the proposed algorithm.The experimental results verify that the proposed partial order improved bat algorithm is superior to other algorithms in most examples.
作者
李婷
张楠
吕志民
邹蕾
LI Ting;ZHANG Nan;LU Zhi-min;ZOU Lei(Beijing Jinghang Research Institute of Computing and Communication,Beijing 100074,China;Collaborative Innovation Center of Steel Technology,University of Science and Technology Beijing,Beijing 100083,China)
出处
《科学技术与工程》
北大核心
2020年第33期13735-13739,共5页
Science Technology and Engineering
基金
国家自然科学基金(51274043)。
关键词
离散蝙蝠算法
旅行商问题
偏序对
组合优化问题
discrete bat algorithm
traveling salesman problem
partial order pair
combinatorial optimization problem
