Developing Dynamic Facility Layout Problem with Single-Solution and Population-Based Metaheuristics Methods

In modern societies, production centers should be able to supply the variety of demand and type of productions correctly, exactly, clearly and straightly. So, this study aims to present the dynamic facility layout problem (DFLP) in order to minimize the total cost of the facilities and costumes. Design an optimal plan leads to reduce the production process and cost of inventory. Transportation cost plays a key-role to specify the performance designing of part systems. This content displays the Dynamic Facility Location Problem (DFLP) in this paper. In order to handle the proposed problem, five metaheuristic methods are introduced: Genetic Algorithm (GA), Simulated Annealing (SA), Tabu Search (TS), Particle Swarm Optimization (PSO) and Imperialist Competitive Algorithm (ICA) are tackled to solve the problem. Taguchi approach is considered to select the proper values for presented algorithms. The results explain that proposed methods are provided the optimal design for the dynamic facility location problem. As a result, ICA and PSO reach the most performance output in the comparison of other algorithms with assumed conditions in the problem.