A hybrid genetic algorithm for component sequencing and feeder arrangement

Ho, William and Ji, Ping (2004). A hybrid genetic algorithm for component sequencing and feeder arrangement. Journal of Intelligent Manufacturing, 15 (3), pp. 307-315.

Abstract

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 travelling distance, or the travelling time, of the placement head. The genetic algorithm developed in the paper hybrisizes 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 travelled by the placement head.

Publication DOI: https://doi.org/10.1023/B:JIMS.0000026569.88191.46
Divisions: Aston Business School > Operations & information management
Aston Business School > Operations & information management research group
Aston Business School
Uncontrolled Keywords: genetic algorithms,heuristics,printed circuit board manufacturing,surface mount technology,component placement sequencing
Full Text Link: http://www.spri ... 1k822623500680/
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Published Date: 2004-06
Authors: Ho, William
Ji, Ping

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