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• Abstract

  In this presentation, we focus on stochastic optimization models for the energy transition. Often, these models are multiscale and include both long-term and short-term periods. In the long run, the focus is often on how to invest in technologies within the energy system, for example, power generation capacities, carbon capture, and storage. Other long-term investments relate to the decarbonization of transport and industry. In the short-term periods, the focus is on storage management and balancing supply and demand. To address uncertainty in both the long and short term, we introduce the concept of multihorizon stochastic programming. This approach allows for uncertainty in both time scales. The structure of these models enables decomposition, and we present computational results for different decomposition methods while discussing how uncertainty affects transition strategies.
• Biography

  Asgeir Tomasgard is a Professor of Operations Research and the Director of NTNU Energy at the Norwegian University of Science and Technology (NTNU). He specializes in decision-making under uncertainty, stochastic optimization, and energy transition strategies, with a focus on sustainable energy systems and energy economics.  Often his research includes developing large-scale optimization models and algorithms to support these within energy systems planning. Tomasgard is on the Management Board of the European Working Group for Stochastic Optimization. He is a member of the European Academies Science Advisory Council (EASAC) Energy Steering Panel and in the board of the Norwegian climate foundation.

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• Abstract

  TBD
• Biography

  Ming Xu is the Chair Professor of Carbon Neutrality, Associate Dean for Research, and Founding Director of Center of Artificial Intelligence for Ecology and Environment in School of Environment at Tsinghua University. Prior to that, he was a Professor in School for Environment and Sustainability and a Professor in Department of Civil and Environmental Engineering at the University of Michigan, Ann Arbor. His research focuses on environmental systems engineering, life cycle assessment, and environmental artificial intelligence. He received the Robert A. Laudise Medal from International Society for Industrial Ecology in 2015,the US National Science Foundation Faculty Early Career Development (CAREER) Award in 2016, the Walter L. Huber Civil Engineering Research Prize from American Society of Civil Engineers in 2021, and the Amazon Research Award in 2024. He was the President of the International Society for Industrial Ecology for 2023-2024. Currently he is the Editor-in-Chief of Elsevier’s flagship journal in environmental management, Resources, Conservation & Recycling, and a member of the UNEP’s International Resource Panel. He has been leading the TianGong Initiative (https://www.tiangong.earth) to develop the TianGong LCA Infrastructure and the world’s first large language model application in environment and sustainability (TianGong AI).

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• Abstract

  Delivering customer orders quickly and cost-effectively requires a well-planned and finely tuned supply chain system.  When a customer visits a product page as well as when an order is placed, multiple systems coordinate to determine a reliable delivery date. This process encompasses verifying item availability, selecting the optimal warehouse to fulfill from, computing the item's path through Amazon's transportation network, and calculating the precise timing of when each fulfillment operation should take place. In particular, when optimizing delivery resources across multiple customer orders, the system identifies potential consolidation and delivery synchronization opportunities evaluating additional delivery options, potentially expediting delivery times while maintaining efficiency. This complex orchestration—managing millions of daily packages across a vast selection of items—relies on Amazon's sophisticated framework of forecasting, planning, and execution systems, powered by advanced optimization models and machine learning algorithms. In this presentation, I will provide a high-level overview of key components within Amazon's fulfillment optimization framework, with particular emphasis on package path computation within the middle mile network.
• Biography

  Luciana Buriol was a professor in the Computer Science Department of the Federal University of Rio Grande do Sul (UFRGS), Porto Alegre, Brazil, for fifteen years. Since May 2021 she is a Principal Research Scientist at Amazon, Seattle/USA. Her background is in Computer Science with Ph.D. in the optimization area (State University of Campinas, Brazil, 2003). She was a visitor Ph.D. student for fifteen months at AT&T Labs (USA, 2001-2002), and a postdoc in the Computer Science Department at the University of Rome “La Sapienza” (Italy, 2004-2005). She was President of the Latin-Ibero-American Association of Operational Research (2012-2014) and Vice-President of IFORS – International Federation of Operational Research Societies (2016-2018).

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• Abstract

  Almost all decisions involve more than one objective, and this is even more relevant today: In addition to financial gains, companies are now expected to consider environmental aspects. The United Nation member states have formulated the 17 goals for sustainable development. However, in general, such objectives are competing, and one has to find a “good” tradeoff between them. Multiobjective optimization delivers important ingredients for finding such a good solution, and, at the same time, helps to understand the dependencies between the objectives.

  In this talk, we give an introduction to multiobjective optimization. Next to presenting basic solution approaches, we emphasize aspects which illustrate that solving such problems poses significantly new challenges compared to focusing on just one objective function, but we also provide strategies for overcoming those.
• Biography

  Gabriele Eichfelder is a full Professor for Mathematical Methods of Operations Research at the Institute of Mathematics of the Technische Universität Ilmenau, Germany. She earned her Doctoral degree in 2006 and completed Habilitation at the Department of Applied Mathematics at the University of Erlangen-Nuremberg, Germany in 2012. She works in the field of Mathematical Optimization with a special interest in nonlinear and global optimization with vector-valued and set-valued objective functions. In addition to fundamental theoretical studies, she has also been working on numerical solvers for applied engineering problems.

  Professor Eichfelder has authored two Springer research monographs, has published extensively in top international journals, and has received several publication awards. She served as program director for the SIAM Activity Group on Optimization 2023-25 and is a co-organizer of the SIAM Conference on Optimization 2026 in Edinburgh. She was a member of the program committee for many conferences, among others the EURO Conference 2021 in Athens and the recent EUROPT conferences. Furthermore, she serves on several editorial boards, among others of the EURO Journal on Computational Optimization, and is as an area editor of the Journal of Optimization Theory and Applications. In 2024, she has been elected EUROPT Fellow by the EUROPT, the EURO Working Group on Continuous Optimization.

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• Abstract

  TBA
• Biography

  Beril Toktay is Professor of Operations Management, Brady Family Chairholder, and Regents' Professor. Her primary research areas are sustainable operations and supply chain management. Professor Toktay's research has been funded by several National Science Foundation grants and has received distinctions such as the 2010 Brady Family Award for Faculty Research Excellence and the MSOM Society's 2015 Management Science Best Paper in Operations Management Award. Her research articles have appeared in Management Science, M&SOM, Operations Research, Production and Operations Management and Industrial Ecology. She became a Distinguished Fellow of the MSOM Society in 2017.

  Professor Toktay served as Associate Editor for M&SOM (2007-2018), POM (2009-2013), and Management Science (2011-2017), and Area Editor (Environment, Energy and Sustainability) for Operations Research (2012-2018). She co-edited the M&SOM Special Issue on the Environment. She was the President of the MSOM Society and VP of Finance of the POM Society. At Georgia Tech, she serves as the Scheller College of Business ADVANCE Professor, a role that is focused on supporting the advancement of women and underrepresented minorities in academia. She is the founding Faculty Director of the Ray C. Anderson Center for Sustainable Business and the co-architect and Executive Co-Director of Georgia Tech's Serve.Learn.Sustain Quality Enhancement Plan.

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• Abstract

  TBA
• Biography

  Andrew is a Senior Principal Research Scientist and a team leader at the CSIRO Environment business unit, based in Brisbane, Australia. He joined CSIRO in 1996, with a passion in developing novel methods to optimise agriculture transport & logistics to increase profitability across the supply chains. From 2012, Andrew led the development of Transport Network Strategic Investment Tool (TraNSIT), which is a state-of-the-art model for assessing and optimising infrastructure investments (road upgrades, use of rail versus road, processing and storage facilities) and analysing the impacts from climate or human induced disruptions. The research has been widely adopted across Australia to inform a $30 billion of major infrastructure investments, saving millions of dollars per year in transport costs, and has also been extended to Vietnam and Indonesia. Andrew received his PhD from Queensland University of Technology in 1996 on the topic of optimising rail freight timetables.