A bi-objective mathematical model toward dynamic cell formation considering labor utilization

This paper addresses dynamic cell formation problem (DCFP) via a new bi-objective mathematical formulation. Although literature body of DCFP includes a vast number of research instances, human-related issues are mostly neglected as an important aspect of DCFP in the corresponding literature. In this paper, the first objective function seeks to minimize relevant costs of the problem including machine procurement and relocation costs, machine variable cost, inter-cell movement and intra-cell movement costs, overtime cost and labor shifting cost between cells, while labor utilization of the modeled DCFP is maximized through the second objective function. Due to NP-hardness of DCFP, an ant colony optimization (ACO) meta-heuristic is developed for the first time in the literature to tackle the problem. Also, authors enhance diversification of the developed algorithm is enhanced by hybridization of the proposed ACO algorithm with a genetic one. Finally, some numerical samples are generated randomly to validate the proposed model by which strengths of the developed algorithm is shown.