| The facility layout problem (FLP) is always one of the most difficult and essential plan duties in the industry. The layout of manufacturing system is related closely to the production rate and cost and a good placement of facilities contributes to the overall efficiency of operations and can reduce operating expenses, so studies of facility layout design have both theoretic and applicable value. During resent decades, a lot of exact and heuristic approaches have been proposed in the literature to solve FLPs. Artificial intelligent heuristic algorithm, such as genetic algorithm (GA) and simulated annealing algorithm (SA) have provided the function formidable algorithm for the facility layout problem because of its algorithm superiority. This dissertation develops two new hybrid intelligent algorithms, in which a partheno-genetic algorithm (PGA), a simulated annealing algorithm and a look-ahead/look-back strategy are assembled in the new algorithms for solving the static and dynamic facility layout problems. The main works are:Firstly, the present dissertation develops a hybrid intelligent algorithm called BGSA_GA to solve the static facility layout problems, which is composed of PGA and SA.We study this algorithm not only in theory but also in examinations. To test the performace of the algorithm, a data set taken from the literature is used in the analysis. The results obtained show that the proposed algorithm is very effective for the large scale static facility layout problems.Secondly, Two hybrid intelligent algorithms are developed to solve the dynamic facility layout problems. The first one is BGSA_GA_D I, which adjusts BGSA_GA to dynamic cases. The second one is the same as BGSA_GA_D I with a look-ahead/look-back strategy added, which is named BGSA_GA_D II. Also, computational work is performed to test the proposed two algorithms. As a result, in these tests the proposed two algorithms found the optimal solutions and performed better than other three heuristic algorithms.At last, the facility layout problem for multiple-floors is considered for further research, in which two approaches for the multi-floor problem are studied. |