NDLI: Multi-Objective Chance Constrained Programming of Spare Parts Based on Uncertainty Theory

Content Provider	Directory of Open Access Journals (DOAJ)
Author	Yi Yang Kunlun Wei Rui Kang Sixin Wang
Abstract	The optimization of spare parts inventory is very important in the modern aerospace engineering system, especially in the environment with low management effectiveness and a wide variety of spare parts. At present, there are many optimization models for spare parts inventory, and the single-objective optimization inventory is mostly used. But the single-objective optimization model has some limitations. First, in the applications of practical engineering, a single-goal decision problem is generally rare, and most of the decisions we have experienced involve many complicated goals. Second, it is difficult to truly present the actual situation when the mathematical programming model is used to discuss the optimization problem in practical engineering application. The solution to solve the model is a hybrid intelligent algorithm by combining the genetic algorithm with the inverse uncertainty distribution function. Finally, an example is given to illustrate the feasibility of the optimization model.
e-ISSN	21693536
DOI	10.1109/ACCESS.2018.2860252
Journal	IEEE Access
Volume Number	6
Language	English
Publisher	IEEE
Publisher Date	2018-01-01
Publisher Place	United States
Access Restriction	Open
Subject Keyword	Electrical Engineering. Electronics. Nuclear Engineering Genetic Algorithm Multi-objective Chance Planning Spare Parts Uncertainty Theory
Content Type	Text
Resource Type	Article

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Multi-Objective Chance Constrained Programming of Spare Parts Based on Uncertainty Theory