Robust Optimization of Nonlinear Processes under Uncertainty

Many important questions and challenges in process systems design, operation and control can be typically posed as nonlinear optimization problems. To date, most optimal decision making tools for such problems are mainly based on deterministic mathematical models, where all parameter values in the model are assumed to be known precisely. In practice, however, mathematical models are merely approximate descriptions of the real system, and parameters such as future demands, prices, equipment wearout and process conditions are subject to significant uncertainty. It has been frequently shown that disregarding such uncertainty can lead to severe performance losses, increased costs, and energy/environmental penalties. We propose to develop robust, local and global optimization methods for the efficient solution of such nonlinear optimization problems in the presence of uncertainties. Depending on their nature, uncertainties can be accounted for in a static/proactive or reactive way. Two important industrial applications will be investigated and the developed methods will be applied for the integrated design, optimization and control of process systems under uncertainty.

While the impact of this project is likely to be in several areas, a few key beneficiaries have been particularly identified. First, the methodologies and tools that will be developed in this project will be very important for both the UK and international chemical process industry. Many important decision problems in the chemical process industry require stochastic and robust optimization-based solution approaches, e.g., production planning, scheduling, design and control of chemical processing systems, melt control, blending problems, supply chain management, etc. All these problems are affected by significant uncertainties. In fact, chemical processes are often poorly understood because of the physicochemical complexities. Robustness with respect to model uncertainty is thus essential to ensure effective operation. Moreover, there are substantial uncertainties concerning the availability of resources, the prices and demands of products, the reliability and availability of plants or machines, etc. These are resolved using parametric and/or robust approaches as appropriate. Robustness of the models is also essential to guarantee the operational safety of chemical plants. Second, the natural resource and energy companies will be interested in using the proposed robust optimization tools to support decision making for the supply/transportation of gas, oil and energy and for business development and trading. Since companies such as oil and gas suppliers, energy marketers and traders face a growing and uncertain global energy market, where the uncertainty is caused by multiple factors such as demand and price volatility, political and regulatory developments, the emerge of new undeveloped markets etc., the optimization of the capacity, resources, cost and environmental impact requires that these uncertainties are efficiently analysed and encountered in the decision making process. Robust optimization approaches are well suited for these types of problems. Third, multiproduct and custom manufacturing industry will benefit from the use of the proposed methodologies and tools of this project for the design, optimization and control of innovative processes and products, such as polymerization and hydrogen separation as well as production planning/scheduling. These are highly nonlinear processes with the uncertainties accounting for the complexity of the process or product, model uncertainties, raw material price variability etc. Fourthly, the developers of computational optimization software tools will benefit for the methodologies and tools developed in this project as they will be able to update and improve their current optimization software products with our new methods as well as develop new ones. Finally, the tools that will be developed in this project will also be offered free for academic research and further development, thus distinctly benefiting the wider UK and international academic and research community.