Relevant Publications

Managing Uncertainty in Data-Driven Simulation-Based Optimization

Computers & Chemical Engineering 2019

Gordon Hullen Jianyuan Zhai Sun Hye Kim Anshuman Sinha Matthew Realff Fani Boukouvala

Optimization using data from complex simulations has become an attractive decision-making option, due to ability to embed high-fidelity, non-linear understanding of processes within the search for optimal values. Due to lack of tractable algebraic equations, the link between simulations and…

Machine learning-based surrogate modeling for data-driven optimization: a comparison of subset selection for regression techniques

Optimization Letters 2019

Optimization of simulation-based or data-driven systems is a challenging task, which has attracted significant attention in the recent literature. A very efficient approach for optimizing systems without analytical expressions is through fitting surrogate models. Due to their increased flexibility, nonlinear…

Nonlinear Variable Selection Algorithms for Surrogate Modeling

AIChE Journal 2019

Jianyuan Zhai Fani Boukouvala

Having the ability to analyze, simulate and optimize complex systems is becoming more important in all engineering disciplines. Decision-making using complex systems usually leads to nonlinear optimization problems, which rely on computationally expensive simulations. Therefore, it is often challenging to…

Optimization of black-box problems using Smolyak grids and polynomial approximations

Journal of Global Optimization 2018

C.A. Kieslich F. Boukouvala C.A. Floudas

A surrogate-based optimization method is presented, which aims to locate the global optimum of box-constrained problems using input–output data. The method starts with a global search of the n-dimensional space, using a Smolyak (Sparse) grid which is constructed using Chebyshev extrema…

Global optimization of grey-box computational systems using surrogate functions and application to highly constrained oil-field operations

Computers & Chemical Engineering 2018

B. Beykal F. Boukouvala C.A. Floudas N. Sorek H. Zalavadia E. Gildin

This work presents recent advances within the AlgoRithms for Global Optimization of coNstrAined grey-box compUTational problems (ARGONAUT) framework, developed for optimization of systems which lack analytical forms and derivatives. A new parallel version of ARGONAUT (p-ARGONAUT) is introduced to solve…

Optimal design of energy systems using constrained grey-box multi-objective optimization

Computers & Chemical Engineering 2018

B. Beykal F. Boukouvala C.A. Floudas E.N. Pistikopoulos

The (global) optimization of energy systems, commonly characterized by high-fidelity and large-scale complex models, poses a formidable challenge partially due to the high noise and/or computational expense associated with the calculation of derivatives. This complexity is further amplified in the…

Teaching data-analytics through process design

Computer Aided Chemical Engineering 2018

F. Boukouvala J. Zhai SH Kim

Data-analytics is becoming a very influential tool for decision-making today both in industry and academia. The incorporation of data-driven concepts in the core chemical engineering curriculum would be very beneficial to our graduates, making them competitive in today’s market. The…

Methods and Tools for Design Space Indentification in Pharmaceutical Development

Comprehensive Quality by Design for Pharmaceutical Product Development and Manufacture 2018

F. Boukouvala F.J. Muzzio M.G. Ierapetritou

The need for a more structured approach to process development has been recently identified in the pharmaceutical industry in order to consistently guarantee quality and value to processes and products. The concept of design space (DS) is a key aspect…

Dimensionality reduction for production optimization using polynomial approximations

Computational Geosciences 2017

B. Beykal C.A. Floudas F. Boukouvala E. Gildin N. Sorek

The objective of this paper is to introduce a novel paradigm to reduce the computational effort in waterflooding global optimization problems while realizing smooth well control trajectories amenable for practical deployments in the field. In order to overcome the problems…

ARGONAUT: AlgoRithms for Global Optimization of coNstrAined grey-box compUTational problems

Optimization Letters 2016

F. Boukouvala C.A. Floudas

The algorithmic framework ARGONAUT is presented for the global optimization of general constrained grey-box problems. ARGONAUT incorporates variable selection, bounds tightening and constrained sampling techniques, in order to develop accurate surrogate representations of unknown equations, which are globally optimized. ARGONAUT…

Relevant Presentations

Data-Centric Optimization: Methods and Applications

2015 AIChE Annual Meeting in Exhibit Hall 1 (Salt Palace Convention Center)

November 08, 2015

F. Boukouvala

As an engineering community we have been working towards developing detailed mathematical simulation models which accurately capture the behavior of complex systems. This trend is reinforced by our drive to couple multiscale information which ranges from the atomistic and molecular…

Constrained Grey-Box Global Optimization of High Dimensional Problems

2015 AIChE Annual Conference in Salon F (Salt Lake Marriott Downtown at City Creek)

November 11, 2015 at 12.55

C.A. Floudas F. Boukouvala

The use of deterministic global optimization methods based on analytical C2 functions is prohibitive in a large portion of engineering applications which have one or multiple of the following characteristics: (a) high computational cost which implies that the calculation of derivatives…

Global Optimization of Constrained Grey-Box Computational Problems

World Congress on Global Optimization 2015 in Gainesville, Florida

February 24, 2015

C.A. Floudas F. Boukouvala

Grey-box global optimization refers to problems for which derivatives of the objective function and/or constraints of the original model are not directly employed for obtaining the global optimum. In typical applications of grey-box optimization, derivative information is either: (1) available…

Argonaut: Algorithms for Global Optimization of Constrained Grey-Box Computational Problems

2014 AIChE Annual Meeting in Atlanta

November 19, 2014

F. Boukouvala C.A. Floudas

Constrained grey-box optimization methods do not employ derivative information of the objective function and/or constraints of the original model for obtaining the global optimum. In typical applications of the above methods, derivative information may be available but deceptive or prohibitively…

Optimization of CO2 Capture, Utilization and Sequestration (CCUS) Supply Chain Networks

2013 AIChE Annual Meeting in San Fransisco

November 08, 2013

M.M.F. Hasan F. Boukouvala C.A. Floudas

CO2 capture, utilization and storage (CCUS) is an enabling technology toward reducing CO2 emissions from stationary sources which include power plants, cement production plants, iron and steel plants, refineries, petrochemicals and gas processing plants. More than 60% of the total…

Global Optimization of Grey-Box Constrained Models

2013 AIChE Annual Meeting in San Fransisco

November 05, 2013

F. Boukouvala M.M.F. Hasan C.A. Floudas

Grey-box optimization methods have a wide range of applicability in various fields which rely on expensive simulations or solely input-output data [1]. Consequently, there has been great interest in the development of methods for the optimization of models for which…

Simulation-Based Derivative-Free Optimization for Computationally Expensive Functions

2012 AIChE Annual Meeting in Pittsburgh

October 31, 2012

F. Boukouvala M.G. Ierapetritou

Nowadays, the need to develop predictive models for complex processes along with advances in computational tools and capabilities have lead to the development of a plethora of detailed complex mathematical methods. However, as the complexity and level of detail increases,…

From Experimental Data to Building Integrated Dynamic Flowsheet Models for Pharmaceutical Processes

2012 AIChE Annual Conference in Pittsburgh

October 29, 2012

F. Boukouvala F.J. Muzzio M.G. Ierapetritou

FDA harmonization guidelines [1] aim to promote building quality into design of pharmaceutical processes through mechanistic understanding of powder process behavior. Based on this paradigm, the industry is moving with a fast pace towards a model-based process and product design,…