Advances in Mathematical Programming Models for Enterprise-wide Optimization

Enterprise-wide optimization (EWO) has become a major goal in the process industries due to the increasing pressures for remaining competitive in the global marketplace. EWO involves optimizing the operations of supply, manufacturing and distribution activities of a company to reduce costs, inventories and environmental impact, and to maximize profits and responsiveness. Major operational items include planning, scheduling, real-time optimization and control. We provide an overview of EWO in terms of a mathematical programming framework. We first provide a brief overview of mathematical programming techniques (mixed-integer linear and nonlinear optimization methods), as well as decomposition methods, stochastic programming and modeling systems. We then address some of the major issues involved in the modeling and solution of these problems. Based on the EWO program at the Center of Advanced Process Decision-making at Carnegie Mellon, we show the scope of these models by describing several applications that include optimal refinery planning, simultaneous planning and scheduling in multisite facilities for continuous multiproduct plants, optimization of industrial gas distribution systems, design and planning under uncertainty of offshore oil field infrastructures, and optimization of responsive supply chain design and planning with demand uncertainty. Finally, we close with a brief discussion of future directions of research in the EWO area.