A hybrid genetic algorithm for mixed model assembly line balancing problem with parallel workstations and zoning constraints

AKPINAR Ş., Bayhan G. M.

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, vol.24, no.3, pp.449-457, 2011 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 24 Issue: 3
  • Publication Date: 2011
  • Doi Number: 10.1016/j.engappai.2010.08.006
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.449-457
  • Keywords: Mixed-model assembly line balancing problem, Genetic algorithm, Hybrid, Parallel workstation assignment, Zoning constraints, HEURISTIC METHOD
  • Dokuz Eylül University Affiliated: Yes


In this paper, we propose a hybrid genetic algorithm to solve mixed model assembly line balancing problem of type I (MMALBP-I). There are three objectives to be achieved: to minimize the number of workstations, maximize the workload smoothness between workstations, and maximize the workload smoothness within workstations. The proposed approach is able to address some particular features of the problem such as parallel workstations and zoning constraints. The genetic algorithm may lack the capability of exploring the solution space effectively. We aim to improve its exploring capability by sequentially hybridizing the three well known heuristics, Kilbridge & Wester Heuristic, Phase-I of Moodie & Young Method, and Ranked Positional Weight Technique, with genetic algorithm. The proposed hybrid genetic algorithm is tested on 20 representatives MMALBP-I and the results are compared with those of other algorithms. (C) 2010 Elsevier Ltd. All rights reserved.