Study On Flow Shop Scheduling Problem Based On Improved Genetic Algorithm

With the current rapid development of manufacturing, advanced manufacturing increasingly high level of production planning and scheduling the workshop production requirements are also increasing. In the past, production scheduling workshop mainly rely on the experience of the workers, there is no theoretical existence of a system, and even now many domestic manufacturers still mired in the production experience led the workshop production scheduling. As many scholars to study the deepening, more intelligent calculation method applied to the production scheduling them to, for example, genetic algorithms, simulated annealing algorithm, PSO and the like.Shop schedule is broadly divided into two, one is the flow scheduling shop, the other one is for job scheduling shop. In many cases job scheduling shop model can also be converted to the flow scheduling shop, so this flow shop selected for the study,it will be applied to the flow shop based on genetic algorithm. Standard genetic algorithm invisible parallelism can quickly get the global optimal solution, but in practice the process, also found a lot of problems exist in the standard genetic algorithm, such as fast convergence, the phenomenon of local optima. This article focused on genetic algorithm to improve the problems, we propose a coding, crossover, mutation of several improved genetic algorithm process, with the final programming using MATLAB, after the draw that improved genetic algorithm is better than standard genetic algorithm.