Scheduling, planning, and investment policy making in process industry using mixed integer optimization

Abstract

This study adopts mixed integer optimization technique to develop novel mathematical models and efficient solution methods for the scheduling, production planning, and investment planning problems of the process industry. First, the problem of refinery short term scheduling of crude oil unloading with inventory management is addressed. In this problem we consider inventory management of a refinery that imports several types of crude oil which are delivered by different vessels. This problem involves optimal operation of crude oil unloading, its transfer from storage tanks to charging tanks, and the charging schedule for each crude oil distillation unit. A mixed-integer optimization model is developed which relies on time discretization. The problem involves bilinear equations due to mixing operations. However, the linearity in the form of a mixed-integer linear programming (MILP) is maintained by replacing bilinear terms with individual component flows. The LP-based branch and bound method is applied to solve the model, and several techniques such as priority branching and bounding, and special ordered sets are implemented to reduce the computation time. This formulation and solution method was applied to an industrial-size problem involving 3 vessels, 6 storage tanks, 4 charging tanks, and 3 crude distillation units over 15 time intervals. To deal with the computational and implementational difficulties indicated in the previous mathematical programming approach, a hybrid refinery scheduling system combining mathematical programming technique and expert system is then proposed. As a mathematical programming technique, mixed-integer linear programming model for crude oil movement between tanks and charging schedule is proposed, while expert system is used to deal with the crude vessel unloading operation. Compared with recent pure mathematical programming approach for the refinery crude oil management, the proposed hybrid refinery scheduling system is shown t...