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计算机科学
旅行商问题
算法
蚁群优化算法
遗传算法
数学优化
粒子群优化
启发式
车辆路径问题
路径(计算)
布线(电子设计自动化)
人工智能
数学
机器学习
计算机网络
程序设计语言
作者
Mohamed Reda,Ahmed Onsy,Mostafa A. Elhosseini,Amira Y. Haikal,Mahmoud Badawy
标识
DOI:10.1016/j.knosys.2022.109290
摘要
Recently, order picking routing (OPR) for robots inside modern warehouses have become one of the most challenging problems. The process of OPR can be formulated as a Travelling Salesman Problem (TSP). Traditional techniques used to solve this problem usually require a long execution time and are problem-specific. Meta-heuristic optimisation techniques have been applied to solve this problem and have shown outstanding results. In this study, we solve the OPR problem using a newly proposed discrete variant of the cuckoo search algorithm. Five modifications were made to the current discrete cuckoo search algorithm. The proposed variant was applied to a traditional TSP problem. Then, the proposed algorithm was customised to solve the OPR problem in a warehouse environment. Finally, the proposed algorithm was applied to a physical prototype. It was then compared with genetic, particle swarm optimisation, and ant colony optimisation algorithms. Simulation and practical results proved the significant performance of the proposed algorithm over all other algorithms, especially in solving complex problems.
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