Research On Dual-resource Multi-objective Flexible Job Shop Scheduling Problem

Job shop scheduling problem (JSP) as the core of the Enterprise Production Management makes an important role in optimum distribution of manufacturing resources and scientific operation. The classical JSP has always being studied by researchers and therefore abundant theories are yielded through the past half centuries. Because there is a certain deviation between the classical JSP and production status of the modern workshop, it is necessary to extend the classical JSP. Dual-resource multi-objective flexible job shop scheduling problem which takes delivery satisfaction, quality, cost, reliability and green attributes as the optimized objects and considers dual-resource constraints of machines and workers is an important extension of JSP. Dual-resource multi-objective flexible job shop scheduling problem takes into not only the flexibility of machine availability, dual-resource constraints, but also the different expectations from different departments. Therefore, research on dual-resource multi-objective flexible job shop scheduling problem is significant both in practice and in theory.Firstly, the optimization objects of scheduling are presented, including delivery satisfaction, quality, cost, reliability and green attributes, then the significance and measurement method of optimization objects are expatiated. Secondly, this paper researches on dual-resource multi-objective flexible job shop scheduling problem in two aspects: certainty and uncertainty. According to the characteristics of dual-resource multi-objective flexible job shop scheduling problem in certain, NSGA-Ⅱis presented to solve this problem; According to the fact that uncertain variables are in the model in uncertainty, the method of grey chance constrained programming is proposed to transform the model, and a method combing grey simulation technology and NSGA-Ⅱis proposed to solve this model. Finally, because a Pareto set is achieved in chapter 4, so it needs to evaluate the Pareto set which can help the enterprise to select the scheduling scheme appropriately. On the basis of subjective and objective weight-giving, least square method is used as a tool to establish an optimization model which determines the weight of indicators. Then, the method of improved TOPSIS is used to evaluate the scheduling scheme, and the effectiveness of the method is verified by example.