Balancing Mass Production Machining Lines with Genetic Algorithms

  • Olga Guschinskaya
  • Evgeny Gurevsky
  • Anton Eremeev
  • Alexandre Dolgui
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 338)


A balancing problem for serial machining lines with multi-spindle heads is studied. The objective is to assign a set of given machining operations to a number of machines while minimizing the line cost and respecting a number of given technological and economical constraints. To solve this problem, three different genetic algorithms are suggested and compared via a series of numerical tests. The results of computational experiments are presented and analyzed.


  1. 1.
    Baybars, I.: A survey of exact algorithms for the simple assembly line balancing. Management Science 32, 909–932 (1986)zbMATHCrossRefMathSciNetGoogle Scholar
  2. 2.
    Baykasoğlu, A., Özbakir, L.: Stochastic U-line balancing using genetic algorithms. The International Journal of Advanced Manufacturing Technology 32, 139–147 (2007)CrossRefGoogle Scholar
  3. 3.
    Dolgui, A., Finel, B., Guschinsky, N.N., Levin, G.M., Vernadat, F.B.: MIP approach to balancing transfer lines with blocks of parallel operations. IIE Transactions 38, 869–882 (2006)CrossRefGoogle Scholar
  4. 4.
    Dolgui, A., Guschinskaya, O., Eremeev, A.: MIP-based GRASP and genetic algorithm for balancing transfer lines. In: Maniezzo, V., Stützle, T., Voß, S. (eds.) Matheuristics, Annals of Information Systems, vol. 10, pp. 189–208. Springer US, Heidelberg (2010)Google Scholar
  5. 5.
    Ghosh, S., Gagnon, R.: A comprehensive literature review and analysis of the design, balancing and scheduling of assembly systems. International Journal of Production Research 27, 637–670 (1989)CrossRefGoogle Scholar
  6. 6.
    Guschinskaya, O., Dolgui, A.: Équilibrage des lignes d’usinage à boîtiers multibroches avec la méthode GRASP. In: Actes de la 7ème Conférence Internationale de Modélisation et Simulation (MOSIM 2008), vol. 2, pp. 1121–1130 (2008)Google Scholar
  7. 7.
    Guschinskaya, O., Dolgui, A.: A transfer line balancing problem by heuristic methods: industrial case studies. Decision Making in Manufacturing and Services 2, 33–46 (2008)zbMATHMathSciNetGoogle Scholar
  8. 8.
    Guschinskaya, O., Dolgui, A.: Comparison of exact and heuristic methods for a transfer line balancing problem. International Journal of Production Economics 120, 276–286 (2009)CrossRefGoogle Scholar
  9. 9.
    Holland, J.H.: Adaptation in natural and artificial systems. University of Michigan Press (1975)Google Scholar
  10. 10.
    Reeves, C.R.: Feature article – genetic algorithms for the operations researcher. INFORMS Journal on Computing 9, 231–250 (1997)zbMATHCrossRefGoogle Scholar
  11. 11.
    Scholl, A., Becker, C.: State-of-the-art exact and heuristic solution procedures for the simple assembly line balancing. European Journal of Operational Research 168, 666–693 (2006)zbMATHCrossRefMathSciNetGoogle Scholar

Copyright information

© IFIP International Federation for Information Processing 2010

Authors and Affiliations

  • Olga Guschinskaya
    • 1
  • Evgeny Gurevsky
    • 1
  • Anton Eremeev
    • 2
  • Alexandre Dolgui
    • 1
  1. 1.École Nationale Supérieure des Mines de Saint-ÉtienneSaint-Étienne Cédex 2France
  2. 2.Omsk Branch of Sobolev Institute of Mathematics SB RASOmskRussia

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