TY - JOUR ID - 8742 TI - An Improved DPSO Algorithm for Cell Formation Problem JO - Journal of Industrial and Systems Engineering JA - JISE LA - en SN - 1735-8272 AU - Hafezalkotob, Ashkan AU - Tehranizadeh, Maryam Amiri AU - Sarani Rad, Fatemeh AU - Sayadi, Mohammad Kazem AD - Industrial Engineering college, Islamic Azad university, South Tehran Branch AD - Department of Decision Science and Knowledge Engineering, University of Economic Sciences, Tehran, Iran Y1 - 2015 PY - 2015 VL - 8 IS - 2 SP - 30 EP - 53 KW - Particle Swarm Optimization KW - Simulated Annealing KW - Cellular manufacturing problem KW - meta-heuristic algorithms DO - N2 - Cellular manufacturing system, an application of group technology, has been considered as an effective method to obtain productivity in a factory. For design of manufacturing cells, several mathematical models and various algorithms have been proposed in literature. In the present research, we propose an improved version of discrete particle swarm optimization (PSO) to solve manufacturing cell formation problem effectively. When a local optimal solution is reached with PSO, all particles gather around it, and escaping from this local optimum becomes difficult. To avoid premature convergence of PSO, we present a new hybrid evolutionary algorithm, called discrete particle swarm optimization-simulated annealing (DPSO-SA), based on the idea that PSO ensures fast convergence, while SA brings search out of local optimum. To illustrate the behavior of the proposed model and verify the performance of the algorithm, we introduce a number of numerical examples. The performance evaluation shows the effectiveness of the DPSO-SA. UR - https://www.jise.ir/article_8742.html L1 - https://www.jise.ir/article_8742_85808f67343cdd5bd0c5e0005689c387.pdf ER -