Practical considerations in using model-based optimization for the scheduling and planning of batch/semicontinuous processes

Abstract Over the last few years, there has been a proliferation of research, industry in-house projects, and new products for automating and improving chemical process industry (CPI) scheduling and planning activities. The principal reason for this proliferation has been the increased global competition within the CPI and a concomitant drive to reduce costs and improve profitability. This paper begins with a description of the issues involved in solving scheduling problems, then discusses a model-based framework for addressing these problems, and finally provides techniques by which models can be constructed for practical applications and solved with modest computational effort. The techniques are illustrated with test problems from the literature and, in the case of a CHES challenge problem, we provide the first optimal solution reported to date. A key point throughout the paper is the effectiveness of using multiple layers of problem representation to separate the high level problem description from its lower level mathematical models and the methods used for their solution.