Relevant Publications

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…

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…

Surrogate-based optimization of expensive flowsheet models for continuous pharmaceutical manufacturing

Journal of Pharmaceutical Information 2013

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

Simulation-based optimization is a research area that is currently attracting a lot of attention in many industrial applications, where expensive simulators are used to approximate, design, and optimize real systems. Pharmaceuticals are typical examples of high-cost products which involve expensive…

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…

Mathematical Modeling and Global Optimization for Entire Petrochemical Planning Operations

2014 AIChE Annual Meeting in Atlanta

November 20, 2014

J. Lie F. Boukouvala X. Xiao C.A. Floudas

In the last twenty years, the petrochemical industry has succeeded by creating markets and supplying them with suitable products used to create goods such as plastics, cosmetics, lubricants, and paints. Petrochemical production begins in a refinery that separates crude oils…

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,…

Multivariate Analysis and Reduced Order Modeling Based On Discrete Element Method (DEM) Simulations for a Powder Blender

AIChE Annual Meeting in Minneapolis

October 20, 2011

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

In this work, a set of Discrete Element Method (DEM) simulations are performed based on a computer experimental design for the qualitative and quantitative characterization of a periodic section of a powder blender. Mixing of powders is a crucial operation…

Application of Kriging for dynamic data- driven modeling of pharmaceutical processes

AIChE Annual Meeting in Salt Lake City

November 11, 2010

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

In emergent technologies it is very common that a functional form for the input-output relationships is unavailable and the process behavior is symbolically described using black-box models. This is the case for many pharmaceutical process operations, for which first-principles models…

Design Space of pharmaceutical processes using data-driven based methods

AIChE Annual Meeting in Salt Lake City

November 08, 2010

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

The identification and graphical representation of process design space is very critical in locating not only feasible but also optimum operating variable ranges and design configurations. Design space of a process is the area of the parametric space within which…

Predictive modeling of pharmaceutical processes with missing and noisy data

2009 AIChE Annual Meeting in Nashville

November 12, 2009

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

Current trends in pharmaceutical product development focus on the fundamental understanding and characterization of all process unit operations, which will lead to the development of predictive models in order to minimize the variability in product performance. The pharmaceutical industry is…