Abstract
This paper presents a fuzzy goal programming approach for solving a multi-objective mixed- model assembly line sequencing problem in a just-in-time production system. A mixed-model assembly line is a type of production line that is capable of diversified small lot production and is able to respond promptly to sudden demand changes for a variety of models. Determining the sequence of introducing models to such an assembly line is of particular importance for the efficient implementation of just-in-time (JIT) systems. In this paper, we consider three objectives, simultaneously: minimizing total utility work, total production rate variation, and total setup cost. Because of existence conflicting objectives, we propose a fuzzy goal programming based approach to solve the model. This approach is constructed based on the desirability of decision maker (DM) and tolerances considered on goal values. To illustrate the behavior of the proposed model, some of instances are solved optimally and computational results reported.
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References
Bard, J. F., Dar-El, E. M., Shtub, A. An analytic framework for sequencing mixed model. International Journal of Production Research 1992; 30: 35–48.
Bard, J. F., Shtub, A., Joshi, S. B. Sequencing mixed-model assembly lines to level parts usage and minimize the length. International Journal of Production Research 1994; 32: 2431–2454.
Hyun, C.J., Kim, Y., Kim, Y.K. A genetic algorithm for multiple objective sequencing problems in mixed model assembly lines. Computers and Operations Research 1998; 25(7–8): 675–690
McMullen, P.R. JIT sequencing for mixed-model assembly lines with setups using tabu search Production Planning and Control 9 1998; (5): 504–510
McMullen, P.R. An efficient frontier approach to addressing JIT sequencing problems with setups via search heuristics. Computers and Industrial Engineering 2001a; 41: 335–353.
McMullen, P.R. A Kohonen self-organizing map approach to addressing a multiple objective, mixed-model JIT sequencing problem. International Journal of Production Economics 2001b; 72: 59–71.
McMullen, P.R. An ant colony optimization approach to addressing a JIT sequencing problem with multiple objectives. Artificial Intelligence in Engineering 2001c; 15: 309–317.
Miltenburg, J. Level schedules for mixed-model assembly lines in just-in-time production systems. Management Science 1989; 35(2): 192–207.
Miltenburg, J., Steiner, G., Yeomans, S. A dynamic programming algorithm for scheduling mixed-model just-in-time production systems. Mathematical Computation Modeling 1990; 13: 57–66.
Monden, Y. Toyota production system. Institute if industrial engineers Press. Atlanta, GA: 1983.
Bellman, R.E., Zadeh, L.A. Decision making in a fuzzy environment, Management Sciences 1970; 17: 141–164.
Collette, Y., Siarry, P. Multiobjective Optimization: Principles and Case Studies. Springer, 2003.
Hannan, E.L. Linear programming with multiple goals, Fuzzy Sets and Systems 1981; 6: 235–164
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Rabbani, M., Rahimi-Vahed, A., Javadi, B., Tavakkoli-Moghaddam, R. (2007). A New Approach for Mixed-Model Assembly Line Sequencing. In: Waldmann, KH., Stocker, U.M. (eds) Operations Research Proceedings 2006. Operations Research Proceedings, vol 2006. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69995-8_28
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DOI: https://doi.org/10.1007/978-3-540-69995-8_28
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69994-1
Online ISBN: 978-3-540-69995-8
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