A distribution center location optimization model based on minimizing operating costs under uncertain demand with logistics node capacity scalability

Huixia Cui, Xiangyong Chen, Ming Guo, Yang Jiao, Jinde Cao and Jianlong Qiu

Physica A: Statistical Mechanics and its Applications, 2023, vol. 610, issue C

Abstract: Logistics center location optimization is one of the core issues in the study of logistics networks. A sensible logistics center distribution can improve the efficiency of goods transportation and the operation efficiency of logistics enterprises. In this paper, we study the problem of optimizing the location of logistics distribution centers in logistics networks with the objective of minimizing the operating costs of logistics distribution centers. Then, we presents a distribution center location optimization model based on minimizing operating costs under uncertain demand with logistics node capacity scalability. Firstly, the future goods quantity prediction data of each node is obtained through the grey-residual Markov chain prediction model. Then, a logistics center location optimization model with three node expansion mechanisms is developed with the objective of minimizing the objective function. Finally, by using the forecast data of goods demand obtained by the grey-residual Markov chain prediction method, we conducted simulation experiments on the cost-minimizing logistics center location optimization model under three different node expansion methods. The corresponding simulation results are obtained by particle swarm optimization algorithm to prove the effectiveness of the model.

Keywords: Logistics system; Node scalability; Logistics center location; Grey-residual Markov chain; Particle swarm algorithm (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:610:y:2023:i:c:s0378437122009505

DOI: 10.1016/j.physa.2022.128392

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