Hybrid Fuzzy Knowledge Based FMS Facility Layout with AGV using Imperialist Competitive Algorithm and Genetic Algorithm

The main goal of FMS facility layout decision is to arrange the layout of the work stations to minimize the whole system cost. To meet this goal, in this paper a novel two phase method is presented For FMS problem with the consideration of unequal stations. In the first phase, a computer program is developed based on a Fuzzy AHP approach, for considering the quantitative and qualitative factors among workstations, stored on a knowledge base, to obtain the amount of the material flow between each two stations. Thereafter in the second phase, we optimize the FMS facility layout by utilizing the amount of material flow between stations (obtained in the first phase) by GA and ICA algorithms. Since the transportation system has the most effect on the FMS design, an AGV algorithm is used in order to increase the FMS efficiency and flexibility. Comparing the results of the ICA (first used in facility layout) to the GA algorithm, shows that the two algorithms are similar regarding power, however the ICA algorithm improves much faster.