Genetic algorithm application to the hybrid flow shop scheduling problem

The hybrid flow shop scheduling problem becomes more and more important, and has gained wide attention both in academic and engineering fields. this paper addresses an attempt to evolve genetic algorithm by a particular genetic programming method to solve this problem. In the algorithm proposed in this paper, the representation of chromosome is composed of two subparts: allocation string and sequencing string, which can be encode and decoded easily. In generating initial population, a special constraint of load balancing between parallel machines is used to reduce the number of individuals. And crossover operation and mutation operation based on evolutionary mechanism are used, so that the exploration and exploitation abilities of the algorithm can be well improved. At last, the scheduling problems of steel treatment jobshops in shipyard are used to evaluate the proposed algorithm, and numerical example shows good result.