1. ¹University of Tehran, Tehran, Iran
2. ²Iran University of Science and Technology, Tehran, Iran
3. ³The University of British Columbia, Vancouver, Canada

Correspondence: R. Tavakkoli-Moghaddam, Department of Industrial Engineering, Faculty of Engineering, University of Tehran, P.O. Box: 11365/4563, Tehran, Iran. E-mail: tavakoli@ut.ac.ir

Received August 2005; Accepted March 2007; Published online 20 June 2007.

Abstract

This paper presents an integer-linear programming approach for a cell formation problem (CFP) in a dynamic environment with a multi-period planning horizon. The objectives are to minimize the inter-cell movement and machine costs simultaneously. In dynamic environments, the product mix and demand are different but deterministic in each period. As a consequence, the formed cells in the current period may not be optimal for the next period. Thus, the reconfiguration of cells is required. Reconfiguration consists of re-forming part families, machine groups, and machine relocation. The CFP belongs to the category of NP-hard problems, thus we develop an efficient simulated annealing (SA) method to solve such a problem. The proposed mathematical model is optimally solved and the associated results are compared with the results obtained by the SA run. The results show that the gap between optimal and SA solutions is less than 4%, which indicates the efficiency of the developed SA scheme.