Visualization Of Dynamic Production Scheduling Algorithm And Its Implementation

The Job-Shop scheduling is the core and one of key point of Manufacturing Execution System (MES) research. It has important meaning for improving the use rate of enterprise resources, elevating the product's quality, shorting the delivery period and reducing the cost, raising the enterprise competition level in market economy. On the basis of practice and specialty of Numerical Control Shop Floor of Xi'an Aircraft Industry (group) Company Limited, this thesis investigates and analyzes actual work flow and running method of planning, scheduling, distributing resource in the shop floor, then completes the abstract design of Manufacturing Execution System (MES). Basing on the frame of MES, this thesis aims at Job-Shop scheduling and its' key technology, and establishes the mathematic model of Job-Shop scheduling according to the production practice and management criterion. Genetic Algorithms (GA) is used as optimizing algorithms of scheduling system, and a rule coding the chromosome with job mark in GA is presented. It solves the problem of illegal result with the rule coding in binary method. On the basis of research, a visualized dynamic method with estimate and decision-making of human is realized. At last, a prototype system of production scheduling is realized by the programming of Visual C++, and Benchmark problem is applied to test the GA and the system, and the correctness of the GA and validity of the system are proved.