Axis 4: Real-time decision support

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Cahiers du GERAD

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In this work, we study a class of two-player deterministic finite-horizon difference games with coupled inequality constraints, where both players have two t...

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In this work, we improve the efficiency of Unit Commitment (UC) optimization solvers using a Graph Convolutional Neural Network (GCNN). In power systems, UC ...

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We consider the set of graphs that can be constructed from a one-vertex graph by repeatedly adding a clique or a stable set linked to all or none of the vert...

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Incentive-based demand response aggregators are widely recognized as a powerful strategy to increase the flexibility of residential community microgrid (RCM)...

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Recommender systems provide personalized recommendations to their users for items and services. They do that using a model that is tailored to each user to i...

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We propose new algorithms with provable performance for online binary optimization subject to general constraints and in dynamic settings. We consider the su...

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In this paper, a new model is proposed for the real-time diesel genset optimal dispatch and unit commitment in remote microgrids. The objective is to reduce ...

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The Twelfth Montreal IPSW took place on August 22-26, 2022, and was jointly organized by the Centre de recherches mathématiques (CRM) and the Institute for D...

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An innovative simultaneous stochastic optimization approach is proposed that combines actor-critic reinforcement learning and stochastic mathematical progr...

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In multi-robot missions, relative position and attitude information between robots is valuable for a variety of tasks such as mapping, planning, and formatio...

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Recommender systems provide recommendations to their users for items and services by creating a model tailored to each user to infer their preferences based ...

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Motivated by our collaboration with one of the largest fast-fashion retailers in Europe, we study a two-echelon inventory control problem called the One-Ware...

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We consider online optimization problems with time-varying linear equality constraints. In this framework, an agent makes sequential decisions using only pri...

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Most reinforcement learning methods for adaptive-traffic-signal-control require training from scratch to be applied on any new intersection or after any modi...

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Hybrid renewable energy systems (HRES), which co-locate two or more renewable energy sources, have proven to be promising frameworks for harnessing complemen...

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Thermostatically-controlled loads have a significant impact on electricity demand after service is restored following an outage, a phenomenon known as cold l...

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The Tenth Montreal IPSW took place on August 13-27, 2020, and was jointly organized by the Centre de recherches mathématiques (CRM) and the Institute for Dat...

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This paper studies a stochastic variant of the vehicle routing problem (VRP) where both customer locations and demands are uncertain. In particular, potentia...

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The existing technologies that update geostatistically simulated models of mineral deposits cannot self-learn from incoming new information generated in oper...

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A new mathematical model for stochastic short-term optimization of mining complexes is presented that simultaneously optimizes the short-term extraction sequ...

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