The Research Of Production Scheduling Based On Genetic Algorithm

Currently, the scheduling and sequencing are the key factors in the manufacturing and services fields. In the increasingly competitive market environment, the production scale of enterprises is bigger and bigger. How to make the necessary and reasonable production scheduling to meet customer delivery dates, reducing costs as much as possible are the key parts in ERP system. Production scheduling problem is NP hard problem and also one of the most difficult combinatorial optimization problems. The conventional methods are difficult to solve it, or need a long time. Now, many researchers are applying t a variety of intelligent algorithms to solve production scheduling problems.Genetic algorithm is a stochastic simulation of natural biological evolution search algorithm. The framework of GA is relatively mature; it has better robustness and is widely used in various fields. The current studying of GA for solving scheduling problems becomes a new focus.The subject to study of the thesis is a company of the A. The thesis develops the production scheduling function in ERP system, describes the typical flow shop scheduling problem in detail and builds the mathematical models with discussing the use of classical Genetic algorithm to solve the problem. Then, from the angle of engineering raise the mathematical model on job shop scheduling, proposing a reverse two-point crossover genetic algorithm. The test shows that this algorithm having good effects in solving the classic JSP problems. Finally, describes the core function of ERP system and the design method of the enterprise in discrete production scheduling.