A multi-objective integrated cellular manufacturing systems design with dynamic system reconfiguration

Cellular manufacturing system (CMS)-an important application of group technology-has been recognized as an effective way to enhance the productivity in a factory. As a result of dynamic deterministic demands within the planning horizon, a CMS configuration for a period might not be optimal or even feasible for other planning periods. Consequently, a multi-objective dynamic cell formation problem is presented, where the total cells load variation and sum of the miscellaneous costs are to be minimized simultaneously. The second objective function calculates machine costs, internal part production, intercellular and intracellular material handling, back order, inventory holding and subcontracting. Since in this type of problem, objectives are in conflict with each other, finding an ideal solution (a solution which satisfies all objectives simultaneously) is not possible. Therefore a non-dominated sorting genetic algorithm (NSGAII) is designed for finding Pareto-optimal frontier that decision maker can select her/his slightly solution. Numerical examples have been solved for demonstrate the efficiency of the proposed algorithm.