Frans de Ruiter
Local maxima at Mt. Fuji (2016)
Contact:
Email 1: fjctderuiter at gmail dot com
Email 2: deruiter at cqm dot nl
LinkedIn
I am a data scientist consultant at CQM where I design and implement optimization algorithms for various clients. I am also involved in helping the companies in the process of transforming to and implementing the data science solutions using artificial intelligence, optimization and machine learning.
I have obtained my PhD in Operations Research at Tilburg University in the Netherlands advised by Dick den Hertog and Dimitris Bertsimas from MIT. Prior to starting my PhD research I obtained a degree in Applicable Mathematics (MSc.) from the London School of Economics and a degree in Management Science and Operations Research (MSc.) from Tilburg University. My main research interests are optimization under uncertainty, adaptive multistage optimization with learning and optimization problems that arise in real-world applications. I have published papers in optimization under uncertainty and adaptive optimization.
Recently I taught an optimization class for the JADS data science expert program. Course material can be found here.
Publications
- Dual approach for two-stage robust nonlinear optimization, (with Jianzhe Zhen and Dick den Hertog), submitted to Operations Research, 2018. [Preprint]
- Duality in two-stage adaptive linear optimization: faster computation and stronger bounds, (with Dimitris Bertsimas), INFORMS Journal on Computing, 28 (3), p500-511, 2016. [Preprint] [DOI] [BibTeX]
- The impact of the existence of multiple adjustable robust solutions, (with Ruud Brekelmans and Dick den Hertog), Mathematical Programming, 160 (1), p531-545, 2016. [Article] [DOI] [BibTeX]
- Robust optimization of uncertain multistage inventory systems with inexact data in decision rules, (with Aharon Ben-Tal, Ruud Brekelmans and Dick den Hertog), Computational Management Science, Computational Management Science, 14 (1), p45-77, 2017. [Article] [DOI] [BibTeX] [Slides]
- Applications of integer programming methods to cages, (with Norman Biggs), The Electronic Journal of Combinatorics, 22 (4), p4.35, 2015. [Article] [BibTeX]
- Primal and dual approaches to adjustable robust optimization, PhD thesis Tilburg University, 2017 (Available online here soon). [Code Chapter 1]
Other publications (in Dutch):
- Een dynamisch voorraadprobleem, StatOR, 15 (3), pp 11-14, 2014. [Article]
Talks
- 23th International Symposium on Mathematical Programming (ISMP), Bordeaux (France), July 2018.
- Workshop Robust Optimization, Avignon (France), June 2018.
- INFORMS Annual Meeting, Houston TX (USA), October 2017.
- Conference on Computational Management Science (CMS), Bergamo (Italy), June 2017.
- SIAM Conference on Optimization, Vancouver (Canada), May 2017.
- 53th Dutch Mathematical Congeres: KWG prize finalist presentation, Utrecht (The Netherlands), April 2017.
- AP seminar IBM Watson, Yorktown Heights NY (USA), November 2016.
- INFORMS Annual Meeting, Nashville TN (USA), November 2016.
- 5th International Conference on Continuous Optimization (ICCOPT), Tokyo (Japan), August 2016.
- 2016 Optimization Days Conference, HEC Montreal, Montreal (Canada), May 2016.
- Invited Research Seminar, Erasmus University Rotterdam, Rotterdam (The Netherlands), February 2016.
- 41th Conference on the Mathematics of Operations Research, Lunteren (The Netherlands), January 2016.
- 22nd International Symposium on Mathematical Programming (ISMP), Pittsburgh PA (USA), July 2015.
- 40th Conference on the Mathematics of Operations Research, Lunteren (The Netherlands), January 2015.
- 11th International Conference on Applied Mathematical Optimization and Modelling (APMOD), Warwick (UK), April 2014.
- Annual meeting of the Netherlands Society for Statistics and Operations Research (VVS+OR), Utrecht (The Netherlands), March 2014.
- Management Science seminar series, London School of Economics, London (UK), March 2014.
Teaching
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Introduction to optimization for the experts from industry in the JADS expert program.
I was responsible for the development and presentation of the case studies, as well as assistance during the day itself. See also the course material (including slides, case files and answers) for the 2018 course.
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This course introduces undergraduate econometrics and operations research students to linear optimization. It gives an introduction in the simplex algorithm and introduces the students to modelling linear and integer optimization problems, as well as solving these models using the AIMMS package. I have been involved in this class as a teaching assistant for the tutorials.
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This course presents the foundations of Business Analytics. It provides the students with the tools and techniques for descriptive, predictive and prescriptive analysis as well as techniques to model decision problems in logistics, finance and marketing. I am involved in this class as an instructor.
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Students from a higher education background (HBO in the Netherlands) are here introduced to statistics, including probability theory and hypothesis testing. It provides the students with understanding of basic techniques and how software packages like Excel and SPSS can help them in providing descriptive and predictive analytic reports. I have been involved in this class as a teaching assistant responsible for the tutorials.