Advances in mathematical programming models for enterprise-wide optimization

• Published in: Computers & chemical engineering Vol. 47; pp. 2 - 18
• Main Author: Grossmann, Ignacio E.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 20-12-2012
• Subjects: Mixed-integer programming; Planning; Scheduling; Stochastic programming; Supply chain optimization; Supply chain optimization; Scheduling; Planning; Mixed-integer programming; Stochastic programming
• ISSN: 0098-1354; 1873-4375
• DOI: 10.1016/j.compchemeng.2012.06.038

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 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. Finally, based on the EWO program at the Center of Advanced Process Decision-making at Carnegie Mellon, we describe several applications to show the potential of this area.