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首页> 外文会议>Environmentally Conscious Manufacturing VI; Proceedings of SPIE-The International Society for Optical Engineering; vol.6385 >Solving a Disassembly-to-Order System by using Genetic Algorithm and Weighted Fuzzy Goal Programming
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Solving a Disassembly-to-Order System by using Genetic Algorithm and Weighted Fuzzy Goal Programming

机译：用遗传算法和加权模糊目标规划求解按订单组装系统

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摘要

In this paper, Genetic Algorithm (GA) is used to solve the disassembly-to-order (DTO) problem. DTO is a system where a variety of returned products are disassembled to fulfill the demand for specified numbers of components and materials. The main objective is to determine the optimal number of take-back EOL (end-of-life) products for the DTO system which satisfy the desirable criteria of the system. We implement the Weighted Fuzzy Goal Programming (WFGP) to calculate the fitness values in GA process. We also consider product deterioration which affects the yield rates (e.g., older products tend to have lower yield rates for usable components) and use heuristic procedure to transform the stochastic disassembly yields into their deterministic equivalents. A numerical example is also considered.
机译：本文中，遗传算法（GA）用于解决按订单拆卸（DTO）问题。 DTO是一个系统，其中拆解了各种退货产品，以满足特定数量的组件和材料的需求。主要目的是确定满足系统理想标准的DTO系统的最佳收回EOL（报废）产品数量。我们实施加权模糊目标规划（WFGP）以计算GA过程中的适应度值。我们还考虑了会影响良率的产品变质（例如，较旧的产品可能会降低可用组件的良率），并使用启发式程序将随机分解的良率转化为确定的等价物。还考虑了一个数值示例。

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