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A survey of assembly planning based on intelligent optimization algorithms

  • Jihong Liu*
  • , Sen Zeng
  • *Corresponding author for this work
  • Beihang University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Assembly planning is one of the NP complete problems, which is even more difficult to solve for complex products. Intelligent optimization algorithms have obvious advantages to deal with such combinatorial problems. Various intelligent optimization algorithms have been applied to assembly sequence planning and optimization in the last decade. This paper surveys the state-of-the-art of the assembly planning methods based on the intelligent optimization algorithms. Five intelligent optimization algorithms, i.e. genetic algorithm (GA), artificial neural networks (ANN), simulated annealing (SA), ant colony algorithm (ACO) and artificial immune algorithm (AIA), and their applications in assembly planning and optimization are introduced respectively. The application features of the algorithms are summarized. At last, the future research directions of the assembly planning based on the intelligent optimization algorithms are discussed.

Original languageEnglish
Title of host publicationASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE2008
Pages1135-1141
Number of pages7
EditionPARTS A AND B
DOIs
StatePublished - 2008
EventASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE2008 - Brooklyn, NY, United States
Duration: 3 Aug 20086 Aug 2008

Publication series

NameProceedings of the ASME Design Engineering Technical Conference
NumberPARTS A AND B
Volume3

Conference

ConferenceASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE2008
Country/TerritoryUnited States
CityBrooklyn, NY
Period3/08/086/08/08

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