The Study Of Distribution Method Of Planning And Scheduling Based On The Genetic Algorithms

As advanced manufacturing mode for the 21th business enterprise, distribution shop mode synthesizes many exellent philosophies of manufacturing pattern such as JIT, parallel engineering project, ecellent manufacturing and so on. Its purpose is making out customer satisfied products with the most low cost. Under distribution shop mode, we are faced with how to organize and manage production, which include how to organize dynamic alliance, how to restructure shop and unit, how to arrange producing planning, and how to proceed scheduling. Among them, job-shop scheduling and control technique is the key to achieve producing high-efficiencyly, high-flexibility, and high-dependability. To study and apply an effective scheduling method and optimizing technique have become practised basic of advanced manufacturing technique. This paper studies how to use self-adapted genetic algorithm and hybrid genetic algorithm (GASA) to solve this problem and its application. The author expatiated on the basic structure, coding manners, decoding rules, fitness function selection, self-adapted mutation and crossover operator, the judging flow of chromosome feasibility of the algorithm, finally , put forward the computing result with pattern of data table and GANTT graph. In this paper, the author come to a conclusion that genetic algorithm is an efficient solution to distribution job-shop problem, while GASA is a more superior method than it.