Research And Application Of Flow Shop Scheduling Based On Genetic Algorithm

Flow shop scheduling problem, also known as the job-scheduling problem with the sequence, is the simplified model of many practical Pipeline production scheduling problems. It has a wide range of application both in the discrete manufacturing industry and in the process industry. Therefore, studying it has great theoretical significance and engineering value. Research and resolve scheduling problems can greatly increase production efficiency, thereby enhancing the competitiveness of these enterprises. Because of complexity of modeling, computational complexity, more dynamic binding and more target-oriented features, flow Shop scheduling problem belongs to combinatorial optimization problem areas, and it is proved to be a very complex and difficult combinatorial optimization problems. Its NP Hard features and powerful engineering background makes it be a hot issue in the theoretical and engineering field. In recent years various evolutionary computation methods have been gradually introduced into the production scheduling problem, such as genetic algorithms, simulated annealing algorithm, and heuristic algorithm and so on.Genetic Algorithm is a random search algorithm which simulating the evolution. It suits solving complex optimization problems.In this paper, we use genetic algorithm to work out complex scheduling problem. The main work and results are as follows:1. Summary the formation, development, classification of the production scheduling theory as well as the existed resolves of scheduling problems.2. Studied the basic framework of Flow Shop scheduling. Has studied the algorithm design which based on the genetic algorithm in solving the production scheduling problems. In view of the widespread existence of the production scheduling Problem-oriented in projection. We studied how to solving the production scheduling problem by genetic algorithm, analyzing the convergence and the complexity of the algorithm.3. Established the production process of Ningbo Bowei Group. And also we established the model of basically Flow Shop scheduling and mixed Flow Shop scheduling .we have used actual production data to simulation. Its simulation scheduling data have confirmed the feasibility and the validity about genetic algorithm in solving the scheduling problems in large-scale flow workshop4. We have developed the procedure on the production scheduling by applying Matlab,Visual C++ 6.0 .Through the relevant simulation experiments, and compared with the existing results, we verify the algorithm has a certain degree of increase both in the quality and the operating efficiency.