 Multi-product supply chain scheduling method based on hybrid genetic algorithmLingmin Yang International Journal of Manufacturing Technology and Management, 2025, vol. 39, issue 1/2, 122-136 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. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:ijmtma:v:39:y:2025:i:1/2:p:122-136 Access Statistics for this article More articles in International Journal of Manufacturing Technology and Management from Inderscience Enterprises Ltd |
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