| With the development of economic globalization, market competition is becoming increasingly fierce. If manufacturing enterprises want to win in the competition, the traditional production management mode has to be improved. Scheduling is the core and key technology of production management. Research on effective scheduling and applications of optimization technologies play an important role in improving production efficiency, decreasing production costs etc., so more and more researchers pay attentions to this field. Based on the background of certain manufacturing enterprise, some research on job shop scheduling problem is shown in this dissertation.Firstly, a review on job-shop of domestic and foreign researches is shown, considering the actual job-shop operation, an extensive and systematic study on the is done. After comparative analysis of the existent methods of solving JSP, the Genetic Algorithm is used as the primary method.Then, discuss and analysis of the enterprise actuality is given, design the goal of this system is proposed. The system architecture and the author's task are briefly introduced, and actual production scheduling problem is emphatically analyzed. To breach the weakness of classical job-shop, this dissertation studies the flexible job-shop optimal scheduling problem. Meanwhile, considering multi-objective of shop scheduling and just-in-time production, the mathematical model of flexible job-shop scheduling for multi-objective is established.Finally, according to the above model, a multi-objective optimization algorithm based on GA with alterable-machine constraint is proposed. In this algorithm, two-dimensional encoding method represents the priority dispatching sequence and the machine which is selected to operate, multi-objective optimization functions are used as evaluation, and the pertinent genetic operations can enlarge the population and search space. The digital computation results verify the feasibility of the algorithm. |
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