Study Of Job-Shop Fuzzy Scheduling Based On Multi-Objective Genetic Algorithm

On the basis of the technical review on the domestic and foreign research, this thesis has an extensive and systematic study on the job-shop scheduling by combining fuzzy logic, which has a great importance to improve productivity and reduce cost.Main works and innovations of this dissertation are as follows.1. Considering multi-objective of shop scheduling, the mathematical model of job-shop fuzzy scheduling for multi-objective is established. Meanwhile, a modeling example is given combining the project of Hefei Automobile Axle Co., Ltd. to solve this model and a corresponding genetic algorithm is developed.2. Based on the model with both fuzzy processing time and fuzzy due date, traditional genetic algorithm is improved. A new method focused on optimizing production cost, makespan and profit is proposed. In this method, Steady State Reproduction, Fuzzy Logic, Evolutionary Strategy and Genetic Algorithm are combined to increase the convergence rate and decrease the probability of premature phenomena.3. The corresponding software is developed with the highly visual computer language VB6.0. With the implement of this method in Hefei Automobile Axle Co., Ltd, it is proved to be feasible and efficient.