Improving the genetic algorithms performance in simple assembly line balancing

Tasan S. O., Tunali S.

COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2006, PT 5, cilt.3984, ss.78-87, 2006 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 3984
  • Basım Tarihi: 2006
  • Dergi Adı: COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2006, PT 5
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, EMBASE, MathSciNet, Philosopher's Index, zbMATH
  • Sayfa Sayıları: ss.78-87
  • Dokuz Eylül Üniversitesi Adresli: Hayır

Özet

In this paper, a hybrid CA 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 CA, 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 CA, we implemented it to various benchmark problems and observed that the hybridization of CA with TS improves the solution performance of the balancing problem.