A New Multi-Objective Model for Dynamic Cell Formation Problem with Fuzzy Parameters

This paper proposes a comprehensive, multi-objective, mixed-integer, nonlinear programming (MINLP) model for a cell formation problem (CFP) under fuzzy and dynamic conditions aiming at: (1) minimizing the total cost which consists of the costs of intercellular movements and subcontracting parts as well as the cost of purchasing, operation, maintenance and reconfiguration of machines, (2) maximizing the preference level of the decision making (DM) and (3) balancing intracellular workload. Dynamic CFP divides the planning horizon to smaller periods and considers different product combinations and demands in each period, which may result in cell reconfiguration necessity. Moreover, it is more realistic to take into account the inexact and uncertain (fuzzy) nature of parameters, such as product demand or machine capacity. The main goals of the proposed model is to select a process plan with the minimum cost and also to identify the most appropriate production volume with respect to fuzzy demands and capacities in order to minimize the deviation from the desired production and balanced machine workload.