A hybrid genetic algorithm for sequencing PCB component placement

Authors:
William Ho;Ping Ji
Affiliations:
Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong;Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong (Corresponding author. E-mail: mfpji@polyu.edu.hk)
Venue:
International Journal of Knowledge-based and Intelligent Engineering Systems - Integrated and hybrid intelligent systems in product design and development
Year:
2005

Citing 1
Cited 2

Genetic Algorithms in Search, Optimization and Machine Learning

Genetic Algorithms in Search, Optimization and Machine Learning

Special issue on integrated and hybrid intelligent systems in product design and development

International Journal of Knowledge-based and Intelligent Engineering Systems - Integrated and hybrid intelligent systems in product design and development
Development of a genetic algorithm for component placement sequence optimization in printed circuit board assembly

Computers and Industrial Engineering

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Abstract

A chip shooter machine for electronic components assembly has a movable feeder carrier holding components, a movable X-Y table carrying a printed circuit board (PCB), and a rotary turret having multiple assembly heads. This paper presents a hybrid genetic algorithm to optimize the sequence of component placements for a chip shooter machine. The objective of the problem is to minimize the total traveling distance of the X-Y table or the board. The genetic algorithm developed in the paper hybridizes the nearest neighbor heuristic, and an iterated swap procedure, which is a new improved heuristic. We have compared the performance of the hybrid genetic algorithm with that of the approach proposed by other researchers and have demonstrated our algorithm is superior in terms of the distance traveled by the X-Y table or the board.