Chemical Production Planning And Scheduling Integration Under Uncertainty

Facing the dual challenge of sustainable development and global competition, process industrial supply chain optimization is one of the most important research fields in process system engineering. Supply chain optimization, which based on decision-making of enterprises, involving many procedures such as procurement, production, storage, transportation, sales and so on, which provides lower energy consumption and higher competence of enterprises.Production planning and scheduling are two of the most important decision-making problems in chemical supply chain optimization. They aim to guide unit operation and resource distribution that according to market requirements, material supply and some other production conditions. Production planning and scheduling deal with different scales of problems, but they are related closely. Therefore, it is necessary to integrate planning and scheduling to improve operation efficiency. Besides, as chemical market is changeable, optimizing production under uncertainty is of great importance.This paper aims to study the comprehensive optimization of planning and scheduling integration under uncertainty, the main contents and innovations can be stated as follows:(1) Production planning and scheduling integration:Production planning and scheduling models are established based on time decomposition strategy, then they are integrated by their production relations in each period. The results show that integration model with capacity constraints can reduce the total cost.(2) Production planning and scheduling integration under demand uncertainty:The production demand uncertainty is described by discrete scenarios and the stochastic programming model is used to optimize the production planning and scheduling. Compared to the conventional method, the scenario-based two stage stochastic programming method can achieve operational and economic optimization.(3) Production planning and scheduling integration under supply and demand uncertainty:The production decisions under the dual uncertainty are obtained with stochastic programming model and the decision-making results under different marketing environments are discussed. The results indicated that decision-making focuses on balancing material procurements with production backorders when "demand exceeds supply", and it focuses on balancing material inventories and production inventories when " supply exceeds demand".The advantages of this paper has been demonstrated by the motivating example. In the mathematical model view, the scenario-based stochastic programming model not only describes uncertain factors accurately, but also achieves production operational and economic optimization. And in the solution strategy view, rolling horizon based strategy can transfer the information between planning model and scheduling model efficiently, thus to achieve the consistency between production planning and scheduling results.