Optimization of cellular manufacturing systems design using the hybrid approach based on the ant colony and tabu search techniques

Cellular systems design problems (CSDP) constitute an important issue in the design of cellular manufacturing systems (CMS). A few years back, it emerged as the best alternative in manufacturing systems, representing a compromise between the efficiency of serial and the flexibility of batch production systems. In this paper, we propose a hybrid approach for solving the CSDP for large industrial data sets. This procedure comprises an ant colony optimization (ACO) and the Tabu search (TS) procedure, which is added in order to improve the quality of the ACO solutions obtained. The problem is formulated as a binary integer programming model that might minimize the dissimilarities existing between machines or parts, and that is characterized as an NP-complete model. With this proposed approach, the results obtained show that it is efficient in terms of the quality and computational time of the solutions. To demonstrate the potential ability of the proposed approach, a numerical example has been investigated.