Abstract
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.
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References
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)
Baybars, I.: A survey of exact algorithms for the simple assembly line balancing problem. Manag. Sci. 21, 909–932 (1986)
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)
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)
Rachamadugu, R., Talbot, B.: Improving three quality of workload assignments in assembly lines. Int. J. of Prod. Resear. 29, 619–633 (1991)
Kirkpatrick, S., Gelatt Jr., C.D., Vecchi, M.P.: Optimization by simulated annealing. Sci. 220, 671–680 (1983)
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)
Chiang, W., Urban, T.L.: The stochastic U-line balancing problem: A heuristic procedure. Eur. J. of Oper. Research 175, 1767–1781 (2006)
Holland, H.J.: Adaptation in natural and artificial systems. The University of Michigan Press, Ann Arbor (1975)
Sabuncuoglu, I., Erel, E., Tanyer, M.: Assembly line balancing using genetic algorithms. J. of Intel. Manufact. 11(3), 295–310 (2000)
Gutjahr, A.L., Nemhauser, G.L.: An algorithm for the line balancing problem. Managem. Sc. 11, 308–315 (1964)
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)
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)
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Hager, T., Ahmed, M., Faouzi, M. (2015). A Genetic Algorithm and a Local Search Procedure for Workload Smoothing in Assembly Lines. In: Chouchane, M., Fakhfakh, T., Daly, H., Aifaoui, N., Chaari, F. (eds) Design and Modeling of Mechanical Systems - II. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-17527-0_13
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DOI: https://doi.org/10.1007/978-3-319-17527-0_13
Publisher Name: Springer, Cham
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