数学优化
序列(生物学)
集合(抽象数据类型)
计算机科学
过程(计算)
整数规划
样品(材料)
随机规划
产品(数学)
随机过程
算法
数学
统计
色谱法
遗传学
生物
几何学
操作系统
化学
程序设计语言
作者
HyungWon Kim,Chuljin Park,Dong-Ho Lee
标识
DOI:10.1080/00207543.2018.1432911
摘要
Selective disassembly sequencing is the problem of determining the sequence of disassembly operations to extract one or more target components of a product. This study considers the problem with random operation times in the parallel disassembly environment in which one or more components can be removed at the same time by a single disassembly operation. After representing all possible disassembly sequences using the extended process graph, a stochastic integer programming model is developed for the objective of minimising the sum of disassembly and penalty costs, where the disassembly costs consist of sequence-dependent set-up and operation costs and the penalty cost is the expectation of the costs incurred when the total disassembly time exceeds a threshold value. A sample average approximation-based solution algorithm is proposed that incorporates an optimal algorithm to solve the sample average approximating problem under a given set of scenarios for disassembly operation times. The algorithm is illustrated with a hand-light case and a large-sized random instance, and the results are reported.
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