文献类型：期刊文献

英文题名：A multi-objective algorithm for task scheduling and resource allocation in cloud-based disassembly

作者：Jiang, Hui[1];Yi, Jianjun[1];Chen, Shaoli[1];Zhu, Xiaomin[1]

机构：[1]East China Univ Sci & Technol, Dept Mech Engn, 130 Meilong Rd, Shanghai 200237, Peoples R China

年份：2016

卷号：41

起止页码：239

外文期刊名：JOURNAL OF MANUFACTURING SYSTEMS

收录：;EI(收录号：20164202920560);WOS:【SCI-EXPANDED(收录号:WOS:000390080700021)】；

基金：This work was supported by the Nature Science Fund of China (NSFC) under Grant 50975088, 51275173, 51210105018, 51575186; the Fundamental Research Funds for the Central Universities under Grant WH0913009; the Shanghai Pujiang Program under Grant PJ201000353. Any opinions, findings, and conclusions or recommendations presented in this paper are those of the authors and do not necessarily reflect the views of the above foundation.

语种：英文

外文关键词：Cloud-based disassembly; Multi-objective genetic algorithm; Task scheduling and resource allocation; Cloud manufacturing

摘要：Some manufacturers outsource their disassembly tasks to professional factories, each factory of them has specialized in its disassembly ability. Different disassembly facilities are usually combined to execute disassembly tasks. This study proposes the cloud-based disassembly that abstracts ability of the disassembly factory as the disassembly resource, the disassembly resource is then able to be allocated to execute disassembly tasks. Based on this concept, the cloud-based disassembly system is proposed, which provides the disassembly service according to the user requirement. The disassembly service is the execution plan for disassembly tasks, which is the result of scheduling disassembly tasks and allocating disassembly resources. To formally describe the disassembly service, this paper builds a mathematical model that considers the uncertainty nature of the disassembly process and precedence relationships of disassembly tasks. Two objectives including minimizing the expected total makespan and minimizing the expected total cost of the disassembly service are also discussed. The mathematical model is NP complete, a multi-objective genetic algorithm based on non-dominated sorting genetic algorithm II is designed to address the problem. Computation results show that the proposed algorithm performs well, the algorithm generates a set of Pareto optimal solutions. The user can choose a preferred disassembly service among Pareto optimal solutions. (C) 2016 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.