Abstract
Several factors change the flexibility and the complexity of production systems. The flexibility of the production system means to meet the changing needs of the customers. As flexibility increases the complexity also increases. In this paper, a multi-objective linear programming is proposed to model the trade-off of the complexity and flexibility of a batch production system (BPS). Strategic, tactical and operational decision variables have been considered. Seven objective functions of the proposed model are assumed as flexibility and complexity. Sixteen tactical decision variables are defined to determine the level of the dimensions of flexibilities and complexities. Thirty-four operational decision variables are defined to tune the shop-floor operations. Several sets of constraints considering aspects of flexibility and complexity as well as the conditions of batch production systems have been considered. As the achievement to the objective functions is not possible simultaneously, and there is no unique and concise relation between these objective functions in a typical batch production system so, a fuzzy goal programming (FGP) approach is proposed to solve the model. Moreover, goal programming (GP), Fuzzy GP, multi-choice goal programming (MCGP) and fuzzy MCGP are proposed and used to compare the performance of solution procedures. The superior solution approach among GP, MCGP, FGP, and FMCGP is FMCGP which concurrently considers several aspiration levels for objective functions, maximization of the achievement level of objective functions, and satisfying uncertain preference of fuzzy objectives. An evolutionary algorithm, called non-dominated sorting genetic algorithm (NSGA-II) and a random weighted version of FMCGP are customized to regenerate several non-dominated designs for flexibility-complexity trade-off problem in BPS. The results are promising and the proposed model is capable to set the strategic, tactical and operational variables of a BPS.
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