Article: Effective storage location assignment model based on a genetic simulation annealing algorithm Journal: International Journal of Wireless and Mobile Computing (IJWMC) 2020 Vol.19 No.1 pp.9 - 17 Abstract: Automated warehouses have become the main application equipment in logistics due to their access automation and simple operation. In order to adapt to the increasingly rapid logistics speed, it is necessary to optimise the location assignment of items in the automated warehouse. Firstly, according to the characteristics of the automated warehouse operation environment, the storage location assignment optimisation model with the shortest time of items travelling the warehouse, the minimum distance between related items and the lowest orthocentre of the shelf is proposed. Then according to the characteristics of the optimisation model and the shortcomings of the traditional genetic algorithm (GA), the defects of the GA are improved and the fusion with the simulated annealing algorithm (SA) is completed, so as to form an improved genetic simulation annealing algorithm (SAGA) for the model. Finally, the effectiveness and superiority of the improved fusion algorithm are verified by comparing the SA, the SAGA and the improved SAGA. Inderscience Publishers - linking academia, business and industry through research

Title: Effective storage location assignment model based on a genetic simulation annealing algorithm

Authors: Li Zhou; Xi Yang; Lei Chen; Siqing You; Feng Li; Yang Cao

Addresses: School of Information, Beijing Wuzi University, Beijing 101149, China ' School of Information, Beijing Wuzi University, Beijing 101149, China ' School of Information, Beijing Wuzi University, Beijing 101149, China ' School of Information, Beijing Wuzi University, Beijing 101149, China ' School of Information, Beijing Wuzi University, Beijing 101149, China ' School of Information, Beijing Wuzi University, Beijing 101149, China

Abstract: Automated warehouses have become the main application equipment in logistics due to their access automation and simple operation. In order to adapt to the increasingly rapid logistics speed, it is necessary to optimise the location assignment of items in the automated warehouse. Firstly, according to the characteristics of the automated warehouse operation environment, the storage location assignment optimisation model with the shortest time of items travelling the warehouse, the minimum distance between related items and the lowest orthocentre of the shelf is proposed. Then according to the characteristics of the optimisation model and the shortcomings of the traditional genetic algorithm (GA), the defects of the GA are improved and the fusion with the simulated annealing algorithm (SA) is completed, so as to form an improved genetic simulation annealing algorithm (SAGA) for the model. Finally, the effectiveness and superiority of the improved fusion algorithm are verified by comparing the SA, the SAGA and the improved SAGA.

Keywords: automated warehouse; storage location assignment optimisation; improved SAGA; reversed operator.

DOI: 10.1504/IJWMC.2020.109237

International Journal of Wireless and Mobile Computing, 2020 Vol.19 No.1, pp.9 - 17

Received: 20 Jul 2019
Accepted: 04 Nov 2019
Published online: 02 Sep 2020 *

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Title: Effective storage location assignment model based on a genetic simulation annealing algorithm

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