| With the development of industrial production toward high technology, hyper-integration, complicated management and cooperation of management in many domains, the system of production scheduling has played a more and more important role as a command center of control and management of industrial production process. Production scheduling is that of assigning scarce resources to competing activities over a given time horizon to obtain the best possible system performance. It is proved to be a NP-Complete problem.In order to solve production scheduling problems, people have resorted to many methods among which modeling problems with mathematic programming is the most popular one with the best effect. MILP and MINLP are applied widely in solving production scheduling problems, and MILP is of more research value. However, because of the representing limitation of model itself and the complexity of the real industrial processes, the scheduling models have disadvantages of unreadable expression, tough systematic realization and hyper-framework, which finally makes the models to be solved difficultly. So it is bad way only depend on classical mathematic programming models. So some researchers have focused on the mathematic optimization by introducing logic into mathematical programming in recent years.This paper introduces the three main logic-based model frameworks nowadays and presents a new logic-based generalized disjunctive programming model for batch process scheduling by more suitable generalized disjunctive programming, which is combined with MILP for batch process scheduling based on State-Task Network. In this model Boolean variables substitute for discrete 0-1 variables, constraint branch is represented by disjunction and the production schemes are assigned by logic propositions, which overcome the shortcoming of hyper-framework with 0-1 variables and make the model explicit and flexible. Then, this paper proposes a logic-based... |
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