Study On Jobshop Dynamic Scheduling Based On Genetic Algorithm

The Job-Shop scheduling is an important factor to influence the manufacturing industry production efficiency. It is important for manufacturing enterprises to improve production efficiency, reduce production costs by employing an effective method of scheduling and optimization technology, which is the popular research area currently. This dissertation has analyzed the corresponding demand of Job Shop scheduling. Taking the Job shop static scheduling genetic algorithm as research foundation, this dissertation has further studied Job shop dynamic scheduling strategy based on the genetic algorithm.Firstly, this dissertation introduced both domestic and foreign studies method, development situation and current difficulties about job shop scheduling. The basic concept, principle and method of genetic algorithm are illustrated.Secondly, this dissertation made detailed mathematical analysis to the job shop scheduling, and predigested to mathematics description, established the mathematical model for the static scheduling, improved the code decoding, the adaptation value function and the heredity operator of genetic algorithm. Finally, the result of simulation indicates validity of this algorithm.Thirdly, through the research on the dynamic scheduling question, this dissertation based on the static scheduling of genetic algorithm, studied the dynamic scheduling strategy which dispatches again by the event driven and the periodic actuation unifies. Specific analytical processing is carried out to various dynamic events, and discussed the issue of real-time property in scheduling.Finally, analyzing the functional requirements of Job-Shop scheduling system, determined the function structure of the system. Appling VB language developed optimized prototype system based on genetic algorithm for Job-Shop scheduling, based on the study on Job-Shop scheduling algorithms and scheduling strategies in last few chapters.