Research On Job-Shop Scheduling Problem Of The Cemented Carbide Tool Workshop Based On Hybrid Genetic Algorithm

Job-shop scheduling problems are not only an important issue in practical production of manufacturing system but also one of the difficulties of theoretic research. It has large practical significance and theoretical value.Currently, the manufacturing enterprises of cemented carbide tool also adopt the traditional manual scheduling methods in their workshop. This scheduling has a long cycle but low efficiency. These can't adapt to the complex demands of market, such as short cycle, delivery on time and the improvement of the production's efficiency. Frequent adjustments of production plan often put the whole production into chaos and the urgency. How to resolve the bottlenecks problems of the job-shop scheduling in the production's process and to increase the production's efficiency and product's quality for the enterprises of carbide tool is the key to this research. The paper analyses the environment and characteristics of the production around the characteristics of technics in the process of carbide tool's production and makes a preliminary sketch of the structure of information manufacturing system of carbide tool's production. On base of that, the paper establishes a two-level scheduling system model suitable for the job-shop scheduling status of carbide tool's production. The upper scheduling system takes charge of the deployment of the production task from the control centre to every workshop. The lower is for the implementation of the idiographic production. The paper focuses on the latter and establishes the mathematical optimization model of the job-shop scheduling at the base of production's cycle and delivery on the example of the manufacturing plant's production of molds.Aiming at characteristic of Carbide Tool's production scheduling problems, the paper solves the established job-shop scheduling model using the hybrid genetic algorithm accordingly. The paper presents a staggered evolution of the self-adapted hybrid genetic algorithm and analyzes design process of the algorithm detailedly. In view of the actual situation workshop, the traditional method of coding based on the processes is improved. The example is simulated by MATLAB and the comparative results, by comparing double-objective scheduling with single-objective scheduling and comparing the staggered evolution of hybrid genetic algorithm with standerd genetic algorithm and self-adapted genetic algorithm, show that the scheduling model based on staggered evolution of hybrid genetic can get satisfying results. Finally, further discussion is made about the workshop's dynamic scheduling and multi-objective optimization. At first, we analyze the dynamic scheduling strategy and adopt the re-scheduling method that periodic re-scheduling of variable cycle and event-driven are integrated. Then the paper gives several typical ways to solve the critical issues, and analyze the scheduling problem of multi-objective optimization. The method of confirming the multi-objective weight is based on the Analytic Hierarchy Process. It establishes the foundation for the solving problem of multi-objective dynamic scheduling.