Based On The Research And Application Of Hybrid Genetic Algorithm Shop Scheduling Problem

Shop Scheduling is making plan for the production process of a shop. It's the core of the advanced intelligent, automatic and information technology manufacturing systems. The effective research and application of shop scheduling method and optimization technique can improve the utilization of resource and production efficiency.So, efficient algorithm for shop scheduling is the core and key to solve the shop scheduling problem.Genetic algorithm which is an intelligent search algorithm is a class of simulating biological genetic and evolutionary. Because it is simple, universal, wide range of applications and global optimization capability, it has been widely used in shop scheduling problem.In this paper,Firsrt,the research status of the shop scheduling problem has been analyzed,and the shop scheduling problem has been described and classified. Then the basic idea, the basic elements, algorithmic process of genetic algorithm and the adaptive genetic algorithm, multi-objective genetic algorithm have been discussed. For the reason that genetic algorithm is easy to fall into local optimum, appear premature, and the convergence speed and accuracy still need to be improved, so making use of the simulated annealing algorithm's feature of good local search ability, A hybrid genetic algorithm which is combined with genetic algorithms and simulated annealing algorithm has been proposed to solve the shop scheduling problem.In the concrete application of hybrid genetic algorithm, the first of its application is in the job-shop scheduling problem, and respectively making comparative analysis with a simple genetic algorithm and simulated annealing algorithm.The result is show that the hybrid genetic algorithm has overcomed the inadequate of solving the shop scheduling optimization with a single algorithm. Finally, based on the introduction of Nanjing's cigarette factory, the hybrid genetic algorithm is applied in the tobacco packaging optimization scheduling problems of a cigarette factory's APS system. The tobacco packaging optimization scheduling problems of a cigarette factory is based on delivery time, multi-constrained, with parallel machines and multi-objective flow shop scheduling problem.