A Genetic Algorithm and a Local Search Procedure for Workload Smoothing in Assembly Lines

  • Triki HagerEmail author
  • Mellouli Ahmed
  • Masmoudi Faouzi
Part of the Lecture Notes in Mechanical Engineering book series (LNME)


In this paper, a genetic algorithm and a local search procedure are proposed to minimize workload smoothness index in an extension of Simple Assembly Balancing problem 2 (SALBP-2). The performance criteria considered are the cycle time and the smoothness index before local search procedure, and after local search procedure. The effectiveness of the proposed approach has been evaluated through a set of instances randomly generated.


Balancing Assembly line Precedence and zoning constraints Cycle time Smoothness Index 


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  1. Akpına, S., MiracBayhan, G.: A hybrid genetic algorithm for mixed model assembly line balancing problem with parallel workstations and zoning constraints. Eng. Appl. of Artificial Intel. 24, 449–457 (2011)CrossRefGoogle Scholar
  2. Baybars, I.: A survey of exact algorithms for the simple assembly line balancing problem. Manag. Sci. 21, 909–932 (1986)CrossRefMathSciNetGoogle Scholar
  3. Scholl, A., Becker, C.: State-of-the-art exact and heuristic solution procedures for simple assembly line balancing. Eur. J. of Operat. Research 168, 666–693 (2006)CrossRefzbMATHMathSciNetGoogle Scholar
  4. Mozdgir, A., Mahdavi, I., Seyedi Badeleh, S.I., Solimanpur, M.: Using the Taguchi method to optimize the differential evolution algorithm parameters for minimizing the workload smoothness index in simple assembly line balancing. Mathemati. and Comp. Model. 57, 137–151 (2013)CrossRefzbMATHGoogle Scholar
  5. Rachamadugu, R., Talbot, B.: Improving three quality of workload assignments in assembly lines. Int. J. of Prod. Resear. 29, 619–633 (1991)CrossRefGoogle Scholar
  6. Kirkpatrick, S., Gelatt Jr., C.D., Vecchi, M.P.: Optimization by simulated annealing. Sci. 220, 671–680 (1983)CrossRefzbMATHMathSciNetGoogle Scholar
  7. Miralles, C., Garcia-Sabater, J.P., Andres, C., Cardos, M.: Branch and bound procedures for solving the assembly line worker assignment and balancing problem. Application to sheltered work centres for disabled. Discr. Appl. Math. 156, 352–367 (2008)CrossRefzbMATHMathSciNetGoogle Scholar
  8. Chiang, W., Urban, T.L.: The stochastic U-line balancing problem: A heuristic procedure. Eur. J. of Oper. Research 175, 1767–1781 (2006)CrossRefzbMATHGoogle Scholar
  9. Holland, H.J.: Adaptation in natural and artificial systems. The University of Michigan Press, Ann Arbor (1975)Google Scholar
  10. Sabuncuoglu, I., Erel, E., Tanyer, M.: Assembly line balancing using genetic algorithms. J. of Intel. Manufact. 11(3), 295–310 (2000)CrossRefGoogle Scholar
  11. Gutjahr, A.L., Nemhauser, G.L.: An algorithm for the line balancing problem. Managem. Sc. 11, 308–315 (1964)CrossRefzbMATHMathSciNetGoogle Scholar
  12. Leu, Y.Y., Matheson, L.A., Rees, L.P.: Assembly line balancing using genetic algorithms with heuristic generated initial populations and multiple criteria. Dec. Sc. 15, 581–606 (1994)CrossRefGoogle Scholar
  13. Simaria, A.S., Vilarinho, P.M.: A genetic algorithm based approach to the mixed-model assembly line balancing problem of type II. Comput. & Industri. Engin. 47, 391–407 (2004)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Sfax Engineering SchoolUniversity of SfaxSfaxTunisia
  2. 2.Sousse Engineering SchoolUniversity of SousseSfaxTunisia

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