2022 - Research.com Engineering and Technology in United States Leader Award
2000 - Member of the National Academy of Engineering For leadership in mixed integer nonlinear programming (MINLP) model formulation and solution for process design and operation.
Ignacio E. Grossmann mainly investigates Mathematical optimization, Nonlinear programming, Integer programming, Nonlinear system and Scheduling. His Mathematical optimization study incorporates themes from Algorithm and Work in process. The study incorporates disciplines such as Representation, Heat exchanger, Relaxation, Process engineering and Process in addition to Nonlinear programming.
As part of the same scientific family, Ignacio E. Grossmann usually focuses on Integer programming, concentrating on Linear programming and intersecting with Selection. His study looks at the relationship between Nonlinear system and topics such as Integer, which overlap with Algebraic number. His Scheduling research includes themes of Job scheduler, Net present value and Time horizon.
Ignacio E. Grossmann focuses on Mathematical optimization, Nonlinear programming, Scheduling, Linear programming and Integer programming. His research in Mathematical optimization intersects with topics in Algorithm, Decomposition and Nonlinear system. Nonlinear programming is closely attributed to Branch and bound in his research.
His Scheduling research is multidisciplinary, incorporating perspectives in Electricity and Job shop scheduling.
His primary areas of study are Mathematical optimization, Linear programming, Scheduling, Process engineering and Nonlinear programming. In Mathematical optimization, Ignacio E. Grossmann works on issues like Nonlinear system, which are connected to Integer and Global optimization. His Linear programming study also includes
His research on Scheduling also deals with topics like
His scientific interests lie mostly in Mathematical optimization, Linear programming, Nonlinear programming, Work in process and Nonlinear system. His research in Mathematical optimization is mostly concerned with Solver. Ignacio E. Grossmann combines subjects such as Scheduling, Scheduling system, Customer service and Electric power with his study of Linear programming.
The concepts of his Nonlinear programming study are interwoven with issues in Finite set, Numerical analysis, Applied mathematics and Sequential quadratic programming. His Work in process study integrates concerns from other disciplines, such as Process, Process synthesis and Process management. His Nonlinear system study combines topics in areas such as Quadratic equation, Quadratic programming, Quadratically constrained quadratic program, Quadratic growth and Selection.
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Systematic methods for chemical process design
L.T. Biegler;I.E. Grossmann;A.W. Westerberg.
An outer-approximation algorithm for a class of mixed-integer nonlinear programs
Marco A. Duran;Ignacio E. Grossmann.
Simultaneous optimization models for heat integration—II. Heat exchanger network synthesis
Terrence Fu Yee;Ignacio E. Grossmann.
Systematic Methods of Chemical Process Design
Lorenz T. Biegler;Ignacio E. Grossmann;Arthur W. Westerberg.
An algorithmic framework for convex mixed integer nonlinear programs
Pierre Bonami;Lorenz T. Biegler;Andrew R. Conn;GéRard CornuéJols.
Discrete Optimization (2008)
State-of-the-art review of optimization methods for short-term scheduling of batch processes
Carlos Alberto Mendez;Jaime Cerda;Ignacio E. Grossmann;Iiro Harjunkoski.
A combined penalty function and outer-approximation method for MINLP optimization
J. Viswanathan;I.E. Grossmann.
A structural optimization approach in process synthesis. II: Heat recovery networks
Soterios A. Papoulias;Ignacio E. Grossmann.
Retrospective on optimization
Lorenz T. Biegler;Ignacio E. Grossmann.
Computers and Chemical Engineering
Mariano Martín;Ignacio E. Grossmann;Zdravko Kravanja.
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