Open AccessIntegration Methodology of Spare Parts Supply Network Optimization and Decision-making
Author(s) -
Yadong Wang,
Qin Shi,
Zai-Jin You,
Qiwei Hu
Publication year - 2020
Publication title -
promet
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.315
H-Index - 19
eISSN - 1848-4069
pISSN - 0353-5320
DOI - 10.7307/ptt.v32i5.3445
Subject(s) - spare part , data envelopment analysis , mathematical optimization , computer science , measure (data warehouse) , scheme (mathematics) , cost efficiency , supply chain , mathematics , engineering , data mining , operations management , mathematical analysis , operating system , law , political science
In order to optimize the spare parts supply network, a multi-objective optimization model is established with the objectives of the shortest supply time, the lowest risk, and the minimum supply cost. A decomposition-based multi-objective evolutionary algorithm with differential evolution strategy is introduced to solve the multi-objective model. A series of non-dominated solutions, that is, representing the optimal spare parts supply schemes are obtained. In order to comprehensively measure the performance of these solutions, suitable quantitative metrics are selected, and the secondary goal-based cross-efficiency Data Envelopment Analysis (DEA) model has been used to evaluate the efficiency of the obtained optimal schemes. The improved DEA model overcomes the problems that the efficient units cannot be sorted and the optimal weight is not unique in traditional DEA model. Finally, the self-evaluation efficiency and cross-evaluation efficiency of each scheme are obtained, and the optimal supply scheme is found based on their cross-evaluation efficiency.