Application Of Plant Growth Genetic Algorithm In Production Scheduling

In the current competitive environment, effective scheduling has become a necessary condition for the survival in the market. Companies must meet their commitment to their customers of the submission date, otherwise it will cause significant loss of credibility. For manufacturing process management, production scheduling plays a key role in production management tasks, whether can successful implementation and completion depending on scheduling optimization performance. The study on production scheduling can be mainly divided into two aspects modeling and scheduling algorithm design, this article mainly aims at the scheduling algorithm design. The actual production processing exists many constraints, they increased the complexity and difficulty of the production scheduling, some of the existing production scheduling has been unable to meet the actual production needs. Because of the complexity and difficulty of the production scheduling, the scheduling algorithm need to improve, so an improved optimization scheduling algorithm put forward in this paper, and design a simulation production scheduling system.This paper makes a comprehensive study of the genetic algorithm and the plant growth simulation algorithm, after reading a lot of literatures, this paper proposes a hybrid genetic algorithm based on plant growth simulation algorithm. The nature of the plant phototropism is introduced into the genetic algorithm, the structure of the new algorithm is basically the same as the conventional genetic algorithm, and introduced into two concepts plant growing dynamics to the light and growth hormone concentrations, the global searching ability of the algorithm is enhanced, Based on the concept, the growth point determined by auxin concentration and then generate population, which has good gene. Mixed plant growth genetic algorithm in addition to traditional genetic algorithm has a series of advantages, and also has a faster convergence speed, uneasy to fall into local optimal and other unique advantages, so it can be effectively applied to solving production scheduling problems.In this paper, the improved technology applied to the machine tool accessory manufacturing system platform design and development, and the new algorithm is applied to dynamic production optimization model, solving production scheduling problems existed is feasible and effective.