Research optimization on logistics distribution center location based on adaptive particle swarm algorithm

Optik ◽  
2016 ◽  
Vol 127 (20) ◽  
pp. 8443-8450 ◽  
Author(s):  
Xiang Hua ◽  
Xiao Hu ◽  
Wuwei Yuan
Keyword(s):  
Particle Swarm ◽  
Distribution Center ◽  
Particle Swarm Algorithm ◽  
Logistics Distribution ◽  
Center Location ◽  
Swarm Algorithm ◽  
Distribution Center Location

scholarly journals A Hybridization of Cuckoo Search and Differential Evolution for the Logistics Distribution Center Location Problem

2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Rui Chi ◽  
Yixin Su ◽  
Zhijian Qu ◽  
Xuexin Chi
Keyword(s):  
Differential Evolution ◽  
Optimization Algorithm ◽  
Location Problem ◽  
Cuckoo Search ◽  
Distribution Center ◽  
Metaheuristic Algorithms ◽  
Logistics Distribution ◽  
Center Location ◽  
Mutation Operation ◽  
Distribution Center Location

The location selection of logistics distribution centers is a crucial issue in the modern urban logistics system. In order to achieve a more reasonable solution, an effective optimization algorithm is indispensable. In this paper, a new hybrid optimization algorithm named cuckoo search-differential evolution (CSDE) is proposed for logistics distribution center location problem. Differential evolution (DE) is incorporated into cuckoo search (CS) to improve the local searching ability of the algorithm. The CSDE evolves with a coevolutionary mechanism, which combines the Lévy flight of CS with the mutation operation of DE to generate solutions. In addition, the mutation operation of DE is modified dynamically. The mutation operation of DE varies under different searching stages. The proposed CSDE algorithm is tested on 10 benchmarking functions and applied in solving a logistics distribution center location problem. The performance of the CSDE is compared with several metaheuristic algorithms via the best solution, mean solution, and convergence speed. Experimental results show that CSDE performs better than or equal to CS, ICS, and some other metaheuristic algorithms, which reveals that the proposed CSDE is an effective and competitive algorithm for solving the logistics distribution center location problem.

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