再制造
分类
帕累托原理
数学优化
组分(热力学)
文件夹
多目标优化
重新使用
遗传算法
计算机科学
可靠性工程
工程类
数学
经济
制造工程
算法
金融经济学
热力学
物理
废物管理
作者
Zhigang Jiang,Han Wang,Hua Zhang,Gamini P. Mendis,John W. Sutherland
标识
DOI:10.1016/j.jclepro.2018.10.316
摘要
Recovering valuable components from End-of-Life (EOL) product is regarded as a means to extend remaining useful life and reduce production cost of used components in the context of remanufacturing. There are three value recovery options for each component including new, reuse, and reconditioning, making the value recovery of EOL product a complex combinatorial optimization problem. To obtain the optimal value recovery options portfolio of used components and improve the economic benefits from remanufacturing, a multi-objective optimization method of value recovery is applied to the remanufacturing of EOL product. Firstly, an evaluation criterion in terms of quantified damage level and remaining life of used components is established, which aims to identify value recovery options for each used component. Then, the concept of Life Span Equilibrium (LSE) is proposed and a multi-objective optimization model is established, in which LSE, value recovery efficiency, and cost are taken as the objectives. An adaptive Epsilon-dominance based Strength Pareto Evolution Algorithm (AE-SPEA2) is employed to obtain an optimal value recovery portfolio, and its results are compared with an Elitist-based Non-dominated Sorting Genetic Algorithm (NSGA-II) and a Pareto Envelope based Selection Algorithm (PESA-II). Finally, a used lathe (model C6132) is taken as an example to verify the practicality and effectiveness of the proposed method, the results of which indicate that the proposed method is effective in optimizing the value recovery of EOL product.
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