Research On Shop Production Planning And Scheduling In Intelligent Manufacturing System

The shop production planning and scheduling optimization is very important because of its theoretical and practical significance. The subject is studied in this thesis and several innovations are presented.A new objective estimate model is presented for shop production planning and scheduling.It can deal with the optimization with multi-objective, uncertain objective, and the sub-objective demand of each job. An example of scheduling is given, which proves this method is feasible and reasonable.In order to accelerate the convergence speed and to avoid the earliness, an individual optimization and colony diversity genetic algorithm(IOCDGA) is presented. In IOCDGA, a new matrix representation and the basic manipulation for the genetic operator are presented, and the colony average distance and the colony entropy are difined, and the crossover probability and the mutation probability are controlled by the colony diversity. Computational results show that the algorithm is applicable and the number of iterations is less.For the sake of improving the search ability and efficiency, an integrated operator genetic algorithm(IOGA) is presented, where a new vector representation is presented, and genetic operators are adjusted and united. Computational results are better than the international latest research results.The discrete particle swarm optimization is studied for the need of high efficiency and speediness algorithm in SPPS integration optimization, in which the representation and learn and footing method are presented for the search experince of the individual and colony particle. The implemention of the algorithm is given. Computational results show that the algorithm is better in speed.A general integrated optimization scheme of shop production planning and scheduling(SPPS) is present for an automobile gearbox enterprise. The integrated optimization model of SPPS for the assembly workshop, and the representation of solution of optimization and the analysis of solution space are present. A policy of hierarchical search and the implemention of embed IOGA with two-hierarchy are given.The enterprise production data are computed, and the results is fairer far than the production practice.The integrated optimization model of SPPS for the section of Machining of shaft after heat treatment is presented. A policy of direct search and the implemention of IOGA are given. Examples prove these methods are available and efficient.The study is supported by key project of National Natural Science Foundation.