Adaptive Genetic Algorithm for Optimal Printed Circuit Board Assembly Planning

We present a novel application of the genetic algorithm approach for solving the problem of planning optimal placement/insertion sequence and machine setup in primed circuit board (PCB) assembly. The algorithm starts with feasible solutions and utilizes genetic operators to iteratively generate pote...

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Bibliographic Details
Published inCIRP annals Vol. 42; no. 1; pp. 17 - 20
Main Authors Wong, H., Leu, M.C.
Format Journal Article
LanguageEnglish
Published Oxford Elsevier Ltd 1993
Elsevier
Subjects
Algorithms
Applied sciences
Assembly Machines
Electronic equipment and fabrication. Passive components, printed wiring boards, connectics
Electronics
Exact sciences and technology
Optimization
Optimization
Assembly Machines
Algorithms
Adaptive algorithm
Optimal algorithm
Biological evolution
Assembling
Genetics
Iterative method
Printed circuit
Planning
Machine
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Summary:We present a novel application of the genetic algorithm approach for solving the problem of planning optimal placement/insertion sequence and machine setup in primed circuit board (PCB) assembly. The algorithm starts with feasible solutions and utilizes genetic operators to iteratively generate potentially better solutions in the optimization process, similar to the biological evolution process. We first describe the basic algorithm and its application to optimal planning for some popular PCB assembly machines. We then describe an adaptive genetic algorithm, which has its rates of genetic operators changed automatically during the iterative optimization process. We use a Wilcoxon signed rank test to show its performance improvement over the fixed-rate genetic algorithm
ISSN:0007-8506
DOI:10.1016/S0007-8506(07)62382-8