An Integrated Mathematical Programming Model for a Dynamic Cellular Manufacturing System with Limited Resources

Abstract

This paper proposes an integrated integer nonlinear programming model for a concurrent cell formation and production planning problem in a dynamic cell-manufacturing system (DCMS) with limited resources to setup cells and to procure machines. The proposed model seeks to minimise the total costs associated with the production planning and the cell construction and formation under a dynamic system. To validate the model, it is first converted to a linear programming. Then, a numerical example is presented based on which the branch and bound method is used to solve it employing the Lingo 8 software. Besides, due to NP-hardness of the problem, two meta-heuristic algorithms namely a GA and a PSO are utilised to solve large-scale problems. In addition, the Taguchi method is used to calibrate the parameters of the meta-heuristics in order to find better quality solutions. Computational results confirm the efficiency and the effectiveness of the proposed solution algorithms.