An efficient algorithm for placement sequence and feeder assignment problems with multiple placement-nozzles and independent link evaluation

Julius S. Gyorfi*, Chi-Haur Wu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

We show that the genetic algorithm that Leu et al. described to plan component placement sequences and feeder assignments for pick-and-place printed circuit board assembly tasks is a special case of a more general model that supports multiple placement-nozzles and independent feeder and board link (chromosome) evaluation methods. We also show that independent link evaluation can be used to offset a reduction in the parent link sample space and that these results are better than what can be achieved through link-pair evaluation. These generalizations extend the capabilities of the genetic algorithm to a broader range of manufacturing scenarios.

Original languageEnglish (US)
Pages (from-to)437-442
Number of pages6
JournalIEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans
Volume38
Issue number2
DOIs
StatePublished - Mar 1 2008

Keywords

  • Assembly
  • Genetic algorithms
  • Manufacturing planning
  • Planning

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Human-Computer Interaction
  • Theoretical Computer Science
  • Computational Theory and Mathematics

Fingerprint Dive into the research topics of 'An efficient algorithm for placement sequence and feeder assignment problems with multiple placement-nozzles and independent link evaluation'. Together they form a unique fingerprint.

Cite this