The Research On Optimal Methods And Applications Of Job-Shop Scheduling Problem

Job-Shop Scheduling Problem (which JSSP is short for) is a combinatorial optimum problem that is constrained with time sequence and resource. It ? has been proven in theory that the JSSP is a classical NP-hard problem. So the key of solving this problem is the research and the application of excellent optimal scheduling algorithms.In this paper, advantages and disadvantages of existing genetic algorithm are analyzed, on the basis of the characteristic that the scheduling process possesses alternative process planning, two-layers coding scheme based on working procedure priority and machine constraint is proposed, and the genetic optimization algorithm is achieved. Finally, the influence of genetic generations on scheduling performances is analyzed.According to the effect of vary rules on scheduling results, the heuristic algorithm is designed, which adopts the combination scheduling of single rule and multi-rules. Parts with same processes constraint are analyzed using a lot experiments, and results indicate that perfect scheduling results can be achieved with vary rules combination, consequently avoiding the randomicity in the process of single rule scheduling.The application of ant algorithm in production scheduling is discussed, the advantage and the combination point of ant algorithm on Job-Shopproduction scheduling are analyzed, ant optimal algorithm for Job-Shop scheduling is designed, finally the case validation is processed.Linking the enterprise' s production, the database on production planning and scheduling is analyzed and created. The production system is complicated based on Java Server Pages language and the run of this system shows the feasibility and validity of these scheduling algorithms.