The Location Selection of Logistics Center in City Based on Particle Swarm Optimization

Author:

Huang Yingyi1,Wang Xinyu2,Li Tianci3,Chen Hongyan4

Affiliation:

1. NingboTech University

2. Quanzhou Normal University

3. Fuzhou University

4. Quanzhou University of Information Engineering

Abstract

Abstract The location selection of logistics center has great significance to improve the efficiency of regional logistics and optimize the structure of logistics system. The paper constructs a multi-factor constrained P-median site selection model to optimize the location of logistics centers to improve the efficiency of logistics and optimize the structure of the logistics system in a region. With the comparison of the results of the utility of the optimized layout points solved by the particle swarm algorithm and the immune genetic algorithm, it conclude that the optimal fitness value obtained by the particle swarm algorithm is relatively lower than the other one. It is proved that the particle swarm algorithm of the P-median site selection model under this multi-factor constraint has some reference value for multi-logistics center site selection planning.

Publisher

Research Square Platform LLC

Reference21 articles.

1. Navigating concave regions in continuous facility location problems;Ouyang R;Computers & Industrial Engineering,2020

2. Undesirable Facility Location under Uncertainty: Modeling and Algorithm;Pakravan P;Journal of Production and Operations Management,2019

3. A discrete competitive facility location model with minimal market share constraints and equity-based ties breaking rule;Fernández P;Informatica,2020

4. Y. H. Lee, H. J. Keum, K. Y. Han and W. H. Hong, A hierarchical flood shelter location model for walking evacuation planning,Environmental Hazards, vol.20, no.4,pp.432–455, 2021.

5. A. U. Rehman, M. H. Abidi, U. Umer and Y. S Usmani, Multi-criteria decision-making approach for selecting wind energy power plant locations, Sustainability, vol.11, no.21, pp.6112, 2019.

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