Research on optimal strategy of supply chain based on genetic optimization algorithm

Tianci Huang; Huiting Jia; Jiaxin Lu; Yang Jin; Xiangzhen Jia

doi:10.1117/12.2625423

6 December 2021 Research on optimal strategy of supply chain based on genetic optimization algorithm

Tianci Huang, Huiting Jia, Jiaxin Lu, Yang Jin, Xiangzhen Jia

Proceedings Volume 12085, International Conference on Green Communication, Network, and Internet of Things (GCNIoT 2021); 120850W (2021) https://doi.org/10.1117/12.2625423
Event: 2021 International Conference on Green Communication, Network, and Internet of Things, 2021, Kunming, China

Abstract

This paper mainly studies the optimal cost planning of production enterprises in supply chain management. The research on this problem can effectively reduce the risk of enterprises in the procurement process, enable enterprises to obtain the maximum benefits with the lowest cost, and enhance the market competitiveness of enterprises. First of all, the data in Annex 1 are analyzed and preprocessed to extract three kinds of indicators: supply volume, stability and credit value, and then comprehensively evaluate the quality of suppliers from these three angles. Then the double-objective programming model is used to solve the problem, and the genetic algorithm, subjective weighting method, MATLAB programming calculation and SPSS statistical analysis are used to get the ordering plan and transfer plan in the next 24 weeks, which can meet the production demand and the lowest production cost at the same time. Combined with the premise that the enterprise has sufficient room for capacity improvement, the total supply of all suppliers calculated is the weekly capacity appreciation of the enterprise. At the same time, the order quantity is the supply quantity, so when making the ordering and transshipment plan, we only need to consider the economy of the transshipment plan, through the 0-1 programming model with the lowest loss rate as the objective function, get the raw material ordering plan and transfer plan of the enterprise in the next 24 weeks. Finally, the advantages and disadvantages of the model are analyzed and evaluated. on the basis of improving the shortcomings, it is concluded that the model can also be extended to the sales planning problems faced by enterprises and the scheme selection problems in life.

Citation Download Citation

Tianci Huang, Huiting Jia, Jiaxin Lu, Yang Jin, and Xiangzhen Jia "Research on optimal strategy of supply chain based on genetic optimization algorithm", Proc. SPIE 12085, International Conference on Green Communication, Network, and Internet of Things (GCNIoT 2021), 120850W (6 December 2021); https://doi.org/10.1117/12.2625423

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KEYWORDS

Genetic algorithms

Computer programming

Raw materials

Genetics

Optimization (mathematics)

Analytical research

Statistical analysis

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