What is he best known for?
The fields of study he is best known for:
- Mathematical optimization
- Artificial intelligence
- Mechanical engineering
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.
His most cited work include:
- An outer-approximation algorithm for a class of mixed-integer nonlinear programs (1034 citations)
- Systematic Methods of Chemical Process Design (755 citations)
- Simultaneous optimization models for heat integration—II. Heat exchanger network synthesis (727 citations)
What are the main themes of his work throughout his whole career to date?
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.
He most often published in these fields:
- Mathematical optimization (59.82%)
- Nonlinear programming (17.59%)
- Scheduling (15.02%)
What were the highlights of his more recent work (between 2017-2021)?
- Mathematical optimization (59.82%)
- Linear programming (13.48%)
- Scheduling (15.02%)
In recent papers he was focusing on the following fields of study:
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
- Electric power that connect with fields like Integer programming,
- Supply chain together with Operations research and Reinforcement learning.
His research on Scheduling also deals with topics like
- Development most often made with reference to Shale gas,
- Industrial engineering and Stochastic programming most often made with reference to Electricity.
His studies deal with areas such as Distillation, Heat exchanger, Work and Biomass as well as Process engineering.
His Nonlinear programming study combines topics from a wide range of disciplines, such as Upper and lower bounds, Process and Applied mathematics.
Between 2017 and 2021, his most popular works were:
- A review and comparison of solvers for convex MINLP (68 citations)
- Expanding scope and computational challenges in process scheduling (42 citations)
- Deterministic electric power infrastructure planning: Mixed-integer programming model and nested decomposition algorithm (32 citations)
In his most recent research, the most cited papers focused on:
- Mathematical optimization
- Artificial intelligence
- Programming language
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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