Generalized Disjunctive Programming Model for Multi-periodic Continuous Process Scheduling

In continuous production process, there are many complex equipments and special requirements such as continuity and stability, which are very difficult to be presented in classical MINLP formulations. So the production scheduling for continuous process is more difficult than that for discrete process or batch process. In continuous process, experience rules usually play very important roles. But it is impossible to obtain the optimal solution just according to the rules. A novel Generalized Disjunctive Programming model for multi-periodic continuous process scheduling is proposed. In this model, some logistic constraints and experience rules are represented in disjunctive forms, which make the model more completely. An example is used to illustrate the effectiveness of this method.