Modeling a Manufacturing Cell Design Problem with Extended Fuzzy Multi-Objective Programming

Nowadays, management tends to decision making via some techniques according to environmental conditions. The condition of decision making is inaccurate and vague in organic environments and data are mainly uncertain. Decision making is a difficult process in conditions of uncertainty and vagueness in the manufacturing system. In this situation, it seems that fuzzy methodologies are more suitable tools to fuzzy considerations. This paper presents a new fuzzy integer multi-objective mathematical programming model for the cellular manufacturing systems (CMS) design problem and its solution methodologies. The aim of the proposed model is to handle two important problems of CMS design called cell formation and exceptional elements simultaneously in fuzzy environment for efficient and better CMS design. An efficient CMS design requires concurrent consideration of real life and real time features relevant to the system. The objectives of the model are minimization of the cost of exceptional element elimination, minimization of the number of outer cell operations and maximization of the utilized machine capacity. The model fuzzy parameters are part demand, machine capacity, processing time, budget and the exceptional element's elimination costs. Management wants to reach simultaneous optimal solutions for all objective functions. To illustrate the model, an example problem with fuzzy extension is adopted from literature and computational result and sensitivity analysis are obtained by the new solving model. Also, two well-known performance measures are suggested for this problem and model solutions are investigated by using these performance measures. The model is capable of expressing vagueness of all the system parameters and gives the decision-maker (DM) alternative decision plans for different grades of precision.