A chance constrained programming approach to determine the optimal disassembly sequence

Guangdong Tian, Mengchu Zhou, Jiangwei Chu

Research output: Contribution to journalArticlepeer-review

81 Scopus citations

Abstract

Disassembly planning is aimed to perform the optimal disassembly sequence given a used or obsolete product in terms of cost and environmental impact. However, the actual disassembly process of products can experience great uncertainty due to a variety of unpredictable factors. To deal with such uncertainty, this work presents some chance constrained programming models for disassembly cost from the perspective of stochastic planning. Moreover, two hybrid intelligent algorithms, namely, one integrating stochastic simulation and neural network (NN), and another integrating stochastic simulation, genetic algorithm (GA) and neural network (NN), are proposed to solve the proposed models, respectively. Some numerical examples are given to illustrate the proposed models and the effectiveness of proposed algorithms.

Original languageEnglish (US)
Article number6507618
Pages (from-to)1004-1013
Number of pages10
JournalIEEE Transactions on Automation Science and Engineering
Volume10
Issue number4
DOIs
StatePublished - Oct 18 2013
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Keywords

  • Algorithm
  • disassembly
  • disassembly planning
  • modeling and simulation

Fingerprint

Dive into the research topics of 'A chance constrained programming approach to determine the optimal disassembly sequence'. Together they form a unique fingerprint.

Cite this