Research on Multi-level Inventory Optimization Algorithm of Repairable Spare Parts Based on Two Improved Differential Evolution

doi:10.3901/JME.2020.14.245

Abstract

Abstract: In view of the low quality of the traditional marginal analysis method to solve the multi-level repairable spare parts inventory model, two improved differential evolution algorithms are proposed to solve the model, one is the improved differential evolution algorithm with local search, the other is the improved differential evolution algorithm based on the marginal analysis method. The two algorithms run 20 times respectively, and the upper limit of each iteration is set to 5 000 times, and the same optimal solution is obtained. Compared with the optimal solution obtained by marginal analysis method in published literature, the total inventory cost is reduced by 4.44%, which shows that the two algorithms have certain advantages. In addition, the improved differential evolution algorithm based on the marginal analysis method has obvious advantages over the improved differential evolution algorithm with local search, among which the average value of total inventory cost is 2.41%, the standard deviation of total inventory cost is 63.8% and the average number of iterations is 38.7%. It shows that the improved differential evolution algorithm based on the marginal analysis method has three advantages：optimization level, algorithm stability and algorithm calculation efficiency. It is better than the improved differential evolution algorithm with local search.

Key words: repairable spare parts, multilevel inventory, marginal analysis method, improved differential evolution algorithms

CLC Number:

TG156

GU Tao, LI Sujian. Research on Multi-level Inventory Optimization Algorithm of Repairable Spare Parts Based on Two Improved Differential Evolution[J]. Journal of Mechanical Engineering, 2020, 56(14): 245-253.

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