Research On Multi-objective Optimization For Shop Scheduling

With much change of the market and the diversification of customer need, variety and small batch production mode has become the main way of manufacturing gradually. The study of optimization method for batch scheduling is very important to modernization of advanced manufacturing because of its theoretical and practical significance.The conception, development and the main researches in current and in the future of job shop scheduling are introduced, some research methods are introduced and compared. Basic foundation, process and operations of GA are stated briefly, and the characteristics and theoretic are discussed.On the basis of the concept and meaning of double-objective scheduling and multi-technology processing scheduling, the production scheduling integrated framework graphic and mathematic model based on double-objective multi-technology processing scheduling are established. Based on genetic algorithms, a new scheduling algorithm with multiple process plans and no set up time is proposed, and the algorithm is compared with another scheduling algorithm proposed by Nasr and Elsayed. The results show that the proposed algorithm is correct and excellent. Then, considering the practical production, machining time and set up time are detached, a novel scheduling algorithm with multiple process plans and set up time is addressed, and the result shows the proposed algorithm is well which is compared with no set time scheduling algorithm.Furthermore, the multi-objective scheduling in the flow shop is studied. At first, the author establishes a six-objective mathematic model of flow shop scheduling including makespan and mean flow time and derives the processing sequence to achieve multi-objective optimization in flow shop by changing the weighted coefficient of each objective. Secondly, the author puts forward an improved genetic algorithm which adopts ten-digit natural coding to construct chromosome coding and designs crossover operators and mutation operators. At last, the author devises simulation to the flow shop processing system of four machine tools of six workpieces, the result of which proves the model is correct and the algorithm is effective.