An Improved Pigeon-inspired Optimization Algorithm for Solving Dynamic Facility Layout Problem with Uncertain Demand

摘要

In the layout planning, changes in product demand and uncertainty caused by demand prediction need to be considered simultaneously to cope with the market changes. To this end, a dynamic facility layout problem (DFLP) is studied to optimize cost and area utilization considering the uncertain product demands. An improved multi-objective pigeon-inspired optimization algorithm (IMOPIO) is proposed. A global collaboration mechanism is structured to balance the global and local search. The validity of the proposed approach is demonstrated by an industrial case. The results suggest that the search ability of IMOPIO is better than compared algorithms in solving the proposed problem.