Improved Hybrid Genetic Algorithm For The Hybrid Flow Shop Problem

The Hybrid Flow Shop Problem (in brief HFSP) is one of the typical NP-Hard problems in combinatorial problem. Generally it is hard to exactly get a optimum solution,so the fast and effective approximate algorithm have been needed to solve the problem in reasonable time. The Hybrid Flow Shop Problem is the extension of the Flow Shop Problem and the Parallel Shop Problem, and it is usually seen in flexible line.So it is significance in theory and practice. Genetic Algorithm is a random search and optimization method based on natural selection and genetic mechanism of the living beings. They have been widely applied to many fields.The paper, introduce completly the connection of several shop scheduling problems in the graph theory view firstly .Then according to the character of HFSP, puts forwards a Genetic Algorithm of using a new code, so the search space can comprise all the scheduling of half active scheduling.Add some eminent individuals in the incipient population by heuristic algorithms,enhance the compute speed.During the single dot cross operation,import the athuard ordinal number arrow,simplify the cross operation of the natural sequence.After the variation operation,increase the greed algorithm to search partly. Simulation results by computer show that the new algorithm is efficient and ascendant.