A genetic algorithm for assembly line balancing

Abstract Assembly line balancing is a very important aspect in any mass production setup. However, finding the optimal balance is a very difficult proposition because of the computational complexity involved. Hence sub-optimal solutions are preferred over optimal solutions. In this work, a genetic algorithm (GA) is presented for obtaining good quality solutions for assembly line balancing problems. A major feature of GA is the ability to take care of a variety of objective functions. A modified GA working with two populations, one of which allows infeasible solutions, and exchange of specimens at regular intervals is proposed for handling irregular search spaces. The experimental results obtained with a single population, as well as two populations are encouraging.

[1]  Hon-Shiang Lau,et al.  A Cost-Oriented Approach to Stochastic Line Balancing1 , 1973 .

[2]  Warren H. Thomas,et al.  Balancing Stochastic Assembly Lines , 1973 .

[3]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[4]  Hon-Shiang Lau,et al.  A Total Operating Cost Model for Paced Lines with Stochastic Task Times , 1976 .

[5]  Edward P. C. Kao.  A Preference Order Dynamic Program for Stochastic Assembly Line Balancing , 1976 .

[6]  John F. Kottas,et al.  A stochastic line balancing procedure , 1981 .

[7]  A. Raouf,et al.  A new method for assembly line balancing having stochastic work elements , 1982 .

[8]  James F. Cox,et al.  Multiple criteria approach to the facilities layout problem , 1985 .

[9]  Fred N. Silverman,et al.  A Cost-Based Methodology for Stochastic Line Balancing with Intermittent Line Stoppages , 1986 .

[10]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[11]  Soumen Ghosh,et al.  A comprehensive literature review and analysis of the design, balancing and scheduling of assembly systems , 1989 .

[12]  Gunar E. Liepins,et al.  Genetic algorithms: Foundations and applications , 1990 .

[13]  Dooyoung Shin,et al.  An efficient heuristic for solving stochastic assembly line balancing problems , 1990 .

[14]  GUNAR E. LIEPINS,et al.  Representational issues in genetic optimization , 1990, J. Exp. Theor. Artif. Intell..

[15]  Dana S. Richards,et al.  Distributed genetic algorithms for the floorplan design problem , 1991, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..

[16]  Alice E. Smith,et al.  A genetic approach to the quadratic assignment problem , 1995, Comput. Oper. Res..