A hybrid genetic algorithm for component sequencing and feeder arrangement

William Ho, Ping Ji

Research output: Journal article publicationJournal articleAcademic researchpeer-review

43 Citations (Scopus)


This paper presents a hybrid genetic algorithm to optimize the sequence of component placements on a printed circuit board and the arrangement of component types to feeders simultaneously for a pick-and-place machine with multiple stationary feeders, a fixed board table and a movable placement head. The objective of the problem is to minimize the total traveling distance, or the traveling time, of the placement head. The genetic algorithm developed in the paper hybridizes different search heuristics including the nearest neighbor heuristic, the 2-opt heuristic, and an iterated swap procedure, which is a new improving heuristic. Compared with the results obtained by other researchers, the performance of the hybrid genetic algorithm is superior to others in terms of the distance traveled by the placement head.
Original languageEnglish
Pages (from-to)307-315
Number of pages9
JournalJournal of Intelligent Manufacturing
Issue number3
Publication statusPublished - 1 Jun 2004


  • Component placement sequencing
  • Genetic algorithms
  • Heuristics
  • Printed circuit board manufacturing
  • Surface mount technology

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Artificial Intelligence


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