Academic Journal of Computing & Information Science, 2022, 5(1); doi: 10.25236/AJCIS.2022.050111.
Xuxiang Huang, Binglin Cheng
School of Computer and Information Engineering, Hubei University, Wuhan, Hubei, 430061, China
This paper studies the decision-making problem of raw material ordering and transportation in production enterprises, and establishes the optimal procurement scheme and optimal transportation scheme for production enterprises under different conditions based on genetic algorithm and multi-objective programming. Firstly, five factors affecting the company's decision-making are summarized; Secondly, the analytic hierarchy process (AHP) is used to determine the weight of each impact evaluation factor, and then the comprehensive effect measure matrix is obtained by combining with the multi-objective grey target decision model to rank 402 enterprises, and the 50 most important suppliers were selected.In order to better reflect the materials and transportation model required by the enterprise's production, the mean square deviation of the enterprise's output in the past five years is used to approximate its output in the next 24 weeks. The multi-objective optimization algorithm based on the combination of convergence criteria and genetic algorithm is used to obtain that at least 30 suppliers and 5 transporters should be selected; The sensitivity analysis and stability test of the model are carried out.
Ordering and Transportation, Weighted Grey Target Decision Model, Genetic Algorithm, Multi-Objective Optimization Model
Xuxiang Huang, Binglin Cheng. Research on Raw Material Ordering and Transportation Model Based on Multi-objective Programming and ARIMA. Academic Journal of Computing & Information Science (2022), Vol. 5, Issue 1: 54-58. https://doi.org/10.25236/AJCIS.2022.050111.
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