Title: Multi-product supply chain scheduling method based on hybrid genetic algorithm

Authors: Lingmin Yang

Addresses: College of Management, Hubei University of Education, Wuhan, 430205, China

Abstract: In order to solve the shortcomings of traditional methods such as high Hamming loss value and low demand supply rate, a multi-product supply chain scheduling method based on hybrid genetic algorithm was designed. First, build supply time series, and sort the priority of supply chain scheduling according to the priority attribute values of backup plans in each link of the supply chain closed-loop model. Then, taking the shortest scheduling time as the objective function and the location constraints of the revolving warehouse as the constraints, the scheduling results are obtained by combining the genetic algorithm. In order to avoid the genetic algorithm falling into the local optimum, the simulated annealing algorithm is introduced to solve the global optimal solution of the objective function to achieve the coordinated scheduling of the supply chain. The experimental results show that this method can achieve multi-product supply chain scheduling more reasonably and effectively.

Keywords: genetic algorithm; simulated annealing algorithm; multi-product supply chain; supply chain scheduling; dispatch time; positioning of turnover warehouse.

DOI: 10.1504/IJMTM.2025.144117

International Journal of Manufacturing Technology and Management, 2025 Vol.39 No.1/2, pp.122 - 136

Received: 29 Dec 2022
Accepted: 21 Mar 2023
Published online: 28 Jan 2025 *

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