earticle

영어

The thesis mainly studies bi-criteria no-wait flexible flow shop problem, whose optimi-zation objective is to minimize the maximum completion time and the maximum delay time. This problem is NP hard, yet enjoying important theoretical research value, thereby this thesis proposes elite particle swarm optimization (EPSO) to solve bi-criteria no-wait flex-ible flow shop problem. EPSO algorithm applies five modified heuristic algorithms and random methods to generating initial population. Moreover, for the particle personal best, this thesis puts forward elite crossover algorithm, which retains continuous fragments of the identical workpieces among excellent individuals, avoiding the destruction of good continuity between solutions of workpieces. In addition, in order to avoid algorithm into local optimum, this thesis raises double insertion disturbance algorithm to help particles jump out the local optimal state and expand the feasible search range. For the purpose of effectively evaluating algorithm quality, there is a comparison among EPSO algorithm, PSO algorithm and ICA algorithm in simulation experiment that is respectively aimed at small-scale problem and large-scale scheduling problem, the results of which show that the proposed EPSO algorithm, due to better validity and accuracy, is superior to the PSO algorithm and ICA algorithm.