Improving the genetic algorithms performance in simple assembly line balancing

Tasan S., Tunali S.

ICCSA 2006: International Conference on Computational Science and Its Applications, Glasgow, England, 8 - 11 May 2006, vol.3984 LNCS, pp.78-87 identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 3984 LNCS
  • Doi Number: 10.1007/11751649_9
  • City: Glasgow
  • Country: England
  • Page Numbers: pp.78-87
  • Dokuz Eylül University Affiliated: Yes

Abstract

In this paper, a hybrid GA approach combining genetic algorithm (GA) and tabu search (TS) is proposed to solve simple assembly line balancing problem. As this problem is combinatorial and NP hard in nature, the optimum seeking methods are impractical. Therefore, we proposed a hybrid approach, which unites the advantages and mitigates the disadvantages of the two algorithms. To increase the performance of the hybrid GA, we also optimized the control parameters such as the population size, rate of crossover and mutation. Moreover, to gain more insight on the performance of hybrid GA, we implemented it to various benchmark problems and observed that the hybridization of GA with TS improves the solution performance of the balancing problem. © Springer-Verlag Berlin Heidelberg 2006.