Carnegie Mellon University

Ignacio Grossmann

Ignacio E. Grossmann

Rudolph R. and Florence Dean University Professor, Chemical Engineering

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

Bio

Prof. Ignacio E. Grossmann is the Rudolph R. and Florence Dean University Professor of Chemical Engineering, and former Department Head at Carnegie Mellon University.  He obtained his B.S. degree in Chemical Engineering at the Universidad Iberoamericana, Mexico City, in 1974, and his M.S. and Ph.D. in Chemical Engineering at Imperial College in 1975 and 1977, respectively. After working as an R&D engineer at the Instituto Mexicano del Petróleo in 1978, he joined Carnegie Mellon in 1979. He was Director of the Synthesis Laboratory from the Engineering Design Research Center in 1988-93. He is director of the "Center for Advanced Process Decision-making" which comprises a total of 20 petroleum, chemical and engineering companies. Ignacio Grossmann is a member of the National Academy of Engineering , Mexican Academy of Engineering, and associate editor of AIChE Journal and member of editorial board of Computers and Chemical Engineering, Journal of Global Optimization, Optimization and Engineering, Latin American Applied Research, and Process Systems Engineering Series. He was Chair of the Computers and Systems Technology Division of AIChE, and co-chair of the 1989 Foundations of Computer-Aided Process Design Conference and 2003 Foundations of Computer-Aided Process Operations Conference. He is a member of the American Institute of Chemical Engineers, Institute for Operations Research and Management Science, Mathematical Optimization Society, and American Chemical Society.

Research

Grossmann's research concerns optimal design of water networks, energy integration networks, biofuel plants, offshore oil and gas facilities, shale gas infrastructure and water management, and demand side management. He also works in the areas of mixed-integer programming and multistage stochastic programming.

Projects

Logic-based and Global Optimization

New modeling and solution methods are being developed for linear and nonlinear discrete-continuous optimization problems. These are based on generalized disjunctive programming in which equations and symbolic logic relations are formulated as part of the optimization problem. Based on recent connections with disjunctive programming theory by Balas, new reformulations based on a hierarchy of relaxations are being investigated that exhibit tighter relaxations. These ideas are being translated into algorithms for automatic reformulation and for cutting plane algorithms. Global optimization techniques are also being investigated that exploit the mathematical structure of disjunctions of nonconvex functions.

Optimization of Water, Process and Shale Gas Production Systems

Models and solution techniques based on mixed-integer nonlinear programming are being developed for the synthesis of integrated process water networks, for superstructures of complex distillation, and for design of biofuel processes. For water systems effective global optimization techniques are being investigated. The strategic design of infrastructure and short-term water management for shale gas production is being addressed in which in addition to economics, environmental impact is also included through multiobjective optimization.

Planning, Scheduling and Enterprise-wide Optimization

Mixed-integer and disjunctive optimization models and solution techniques are being developed for the planning and scheduling of batch and continuous process systems, as well as for supply chain optimization of process networks. Major applications include design and planning of off-shore oil and gas field facilities, production and distribution of industrial gases, production of multiple grades of polymers, and maintenance of power systems. The handling of uncertainties and disruptions is being handled through novel multistage stochastic optimization methods, which involve decomposition methods based on Lagrangean relaxation, Benders decomposition and bilevel decomposition.

Ignacio Grossmann talks about optimization models and methods to address problems in process systems engineering. This includes mixed-integer optimization, which can save time and money, as well as use fewer resources and reduce environmental impact in processes like shale gas extraction and biofuels processing. Grossmann is a professor of chemical engineering and the director of the Center for Advanced Process Decision Making.