15 - 17 September 2020
The OR62 Online organisers are proud to announce three plenary speakers, featuring plenary sessions by some of the world’s leading thinkers and innovators in their field. Each speaker will make formal 60-minute presentations.
We introduce a new generation of machine learning methods that provide state of the art performance and are very interpretable. We introduce optimal classification (OCT) and regression (ORT) trees for prediction and prescription with and without hyperplanes. We show that:-
(a) Trees are very interpretable;
(b) They can be calculated in large scale in practical times and;
(c) In a large collection of real world data sets they give comparable or better performance than random forests or boosted trees.
Their prescriptive counterparts have a significant edge on interpretability and comparable or better performance than causal forests. Finally, we show that optimal trees with hyperplanes have at least as much modeling power as (feedforward, convolutional and recurrent) neural networks and comparable performance in a variety of real world data sets.
These results suggest that optimal trees are interpretable, practical to compute in large scale and provide state of the art performance compared to black box methods. We apply these methods to a large collection of examples in personalized medicine, financial services, organ transplantation among others.
Bio: Dimitris Bertsimas is currently the Boeing Professor of Operations Research, the Associate Dean of Business Analytics at the Sloan School of Management, MIT. He received his SM and PhD in Applied Mathematics and Operations Research from MIT in 1987 and 1988 respectively. He has been with the MIT faculty since 1988. His research interests include optimization, machine learning and applied probability and their applications in health care, finance, operations management and transportation. He has co-authored more than 250 scientific papers and five graduate level textbooks.
He is the editor in Chief of INFORMS Journal of Optimization and former department editor in Optimization for Management Science and in Financial Engineering in Operations Research. He has supervised 76 doctoral students and he is currently supervising 25 others. He is a member of the National Academy of Engineering since 2005, an INFORMS fellow, and he has received numerous research and teaching awards including he John von Neumann theory prize for fundamental, sustained contributions to the theory of operations research and the management sciences and the president's award of INFORMS recognizing important contributions to the welfare of society, both in 2019, the Morse prize (2013), the Pierskalla award for best paper in health care (2013), the best paper award in Transportation (2013), the Farkas prize (2008), the Erlang prize (1996), the SIAM prize in optimization (1996), the Bodossaki prize (1998) and the Presidential Young Investigator award (1991-1996).
He has co-founded several companies over the years: Dynamic Ideas, a financial services company, whose assets were sold to American Express in 2002, D2 Hawkeye that was sold to Verisk in 2009, Benefit Sciences, ReClaim, Interpretable-AI, and Savvi Financial. Since March, 2020 he has led a group of 30 doctoral, master, postdoctoral students to study multiple aspects of COVID-19. These efforts are detailed in https://covidanalytics.io/
Inclusive Systemic Evaluation is an emerging evaluation approach, developed in partnership with UN Women. It is designed to deal with the complexity of applying the UN Sustainable Development Goals.
Inclusive Systemic Evaluation is grounded in a key principle of Community OR (COR): that ‘engagement’ and ‘community’ need to be defined in a locally meaningful way to address complex cultural, organizational, social and environmental issues.
In a global development context, Inclusive Systemic Evaluation is part of a larger response to shifting development actors (e.g. donors, multilateral organizations, NGOs and participants) away from narrow understandings of stakeholders and context to a more inclusive process of economic and social development.
Each intervention is seen as an opportunity for people to learn about how to build gender equality, sustainability, and socio-economic justice into action for social change.
Bio: Ellen Lewis (PhD) is a systems thinking consultant who works globally in organisational development and evaluation. Her systemic interventions bring into focus the complexity and interrelatedness of gender equality, environmental sustainability, habitability, and social justice.
Ellen partners with a variety of public, private civil society and academic organizations. She has led projects in Africa, the Arabian Peninsula, Asia, the Caribbean, Europe, Latin America, the United Kingdom and the United States. Currently, she is part of a global evaluation team analysing the commitments of the top food and beverage companies (and their supply chains) to be accountable and transparent regarding their social and environmental impacts.
Ellen is a Fellow at the Centre for Systems Studies at the University of Hull in the United Kingdom. She is bilingual in English and Spanish, and currently resides in Northern California, USA. She is a co-author of the UN Women’s Inclusive Systemic Evaluation for Gender Equality, Environments and Marginalized Voices (ISE4GEMs): A New Approach for the SDG Era (2018)
Multi-reservoir systems require adaptive control policies capable of managing evolving hydroclimatic variability and human demands across a wide range of time scales. However, traditional operating rules are static, ignoring the potential for coordinated information sharing to reduce conflicts between multi-sectoral river basin demands. This study shows how recent advances in multi-objective control enable the design of coordinated operating policies that continuously adapt as a function of evolving hydrologic information.
The benefits of the proposed control innovations are demonstrated for the Red River basin of Vietnam, where four major reservoirs serve to protect the capital of Hanoi from flooding, while also supplying farmers with irrigable water supply and the surrounding region with electric power. Operating policies recently proposed by the Vietnamese government seek to improve coordination and adaptivity in the Red River using a conditional if/then/else rule system that triggers alternative control actions using information on current storage and recent hydrology. However, these simple, discontinuous rules fail to protect Hanoi to even the 100-yr flood.
Our policy diagnostics using time-varying sensitivity analysis illustrate how our proposed operations make better use of coordinated system information to reduce food-energy-water conflicts in the basin. These findings accentuate the need to transition from static rule curves to dynamic operating policies in order to manage evolving hydroclimatic variability and socioeconomic change.
Bio: Dr. Reed’s Decision Analytics for Complex Systems research group has a strong focus on the sustainability of Food-Energy-Water systems given conflicting demands from ecosystem services, expanding populations, and climate change.
The tools developed in Dr. Reed’s group bridge complexity science, risk management, economics, multiobjective decision making, artificial intelligence, and high performance computing. Engineering design and decision support software developed by Dr. Reed is being used broadly in academic, governmental, and industrial application areas with more than 30,000 users globally.
The management modeling tools developed by the Reed Research Group combine multiobjective optimization, high performance computing, and advanced spatiotemporal visualization and uncertainty modeling techniques.