Dynamic facility layout problem with hybrid genetic algorithm

Over the past few decades, many optimal and heuristic algorithms have been designed and published to solve the facility layout problem (FLP). These algorithms are mostly static and assume that the flow of materials among facilities is fixed. However, in today's real-world scenario, manufacturing facilities must operate in a dynamic and market-driven environment in which production rates and production mixes are continuously adapting. The dynamic facility layout problem (DFLP) addresses situations in which the flow among various facilities changes over time. In this paper, we present a hybrid genetic algorithm for the DFLP by incorporating jumping gene operations introduced in the jumping gene genetic algorithm (JGGA) in the form of a local search. A computational study is performed with several existing heuristic algorithms. The experimental results show that the proposed algorithm is effective in dealing with the DFLP.