A hybrid genetic algorithm/fuzzy dynamic programming approach to two-machine flowshop problems

Multistage flowshop problems are considered to be fuzzy optimization problems, whose objective is to minimize total completion time of the two-machine flowshop problem with fuzzy processing times and fuzzy makespan. A solution procedure consisting of a genetic algorithm and fuzzy dynamic programming is proposed to obtain a near-optimal solution for the fuzzy model. The main advantage of this approach lies in the Genetic algorithm´s capability to find the global optimum or quasi-optimums and the fuzzy dynamic programming´s high performance to get a local optimum. Finally, an illustrative example is given to evaluate performance and to clarify the effectiveness of the proposed solution procedure.