Chemical Production Planning Model Research And Its Application

Advanced managerial techniques are important to modern enterprises besides production techniques and equipments. Production planning is a key to chemical CIMS. A good planning scheme makes benefits to reduce the costs and inventories, raises the production efficiency and in order to remain competitive in the global marketplace. It is meaningful and valuable in academic research and applications to make study on the chemical planning problems.In this paper, it introduces the theory of particle swarm optimization algorithm and its applications in the chemical production planning. And it mainly studies the chemical planning models based on the objective to maximize the total profit, minimize the energy consumption and multi-objective. An integrated planning model for continuous multi-product plants that consist of a single processing unit is also studied. The main works of the paper as following:1. A multi-stage, multi-product, multi-constraint, and mixed continuous/batch plants planning problem is studied, and the problem is formulated as a mathematic optimization model based on the objective to maximize the total profit with constraints involved resources, work manufacture processes and production capacity etc. Based on the above model, a minimizing energy consumption model and a multi-objective model are studied.2. Due to the complex nature of planning problems in real-world applications, constraint-handling techniques in evolutionary optimization algorithms are studied and a PSO algorithm with percent-coding and dynamic-bounds coding scheme is proposed to solve constrained optimization problems.3. The integrated planning problem for continuous multi-product plants that consist of a single processing unit is studied. The problem is formulated as a mixed-integer nonlinear programming optimization model that is based on a hybrid time representation. The MINLP model is decomposed into an upper level problem and a lower level problem. A decomposition method based on PSO algorithm is proposed for the problem. Finally, the reason of better performance of decomposition method based on PSO is explained.4. Based on the academic research above, and combination between chemical practice and intelligence algorithms, a chemical planning and scheduling system is developed.