基于免疫遗传算法的工艺设计与调度集成

To realize the concurrent distributed integration of process planning and scheduling, a mathematical model of simulating optimization of process and scheduling was established. The decision space, objective functions, and constraints of the model were defined. A co-evolutionary immune genetic algorithm was proposed to simultaneously optimize the combination of alternative process and production scheduling. Collaborative evolution was realized through the interaction between process population and scheduling population, the affinity and concentration of antibody were used to guarantee the diversity of population, the stimulation of antibody was used to realize immune selection, and the elitism keeping strategy was used to guarantee the convergence of the algorithm. To deal with the characteristics of codes, the uniform crossover and random disturbance mutation were used for the process antibody, whereas the uniform order crossover and reverse mutation were used for the scheduling antibody. Simulation of 10 machines and 10 parts was performed to illustrate the validity of the algorithm.