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Coordination of distributed energy resources is critical for electricity grid management. Although nodal pricing schemes can mitigate congestion and voltage deviations, the resulting prices are not necessarily equitable. In this work, we…

Optimization and Control · Mathematics 2023-12-15 Emmanuel Balogun , Sonia Martin , Anthony Degleris , Ram Rajagopal

The study of Day-Ahead prices in the electricity market is one of the most popular problems in time series forecasting. Previous research has focused on employing increasingly complex learning algorithms to capture the sophisticated…

Applications · Statistics 2024-04-29 Carlos Sebastián , Carlos E. González-Guillén , Jesús Juan

We propose an enhancement to wholesale electricity markets whereby the exposure of consumers to increasingly large and volatile consumer payments arising as a byproduct of volatile real-time net loads -- i.e., loads minus renewable outputs…

Optimization and Control · Mathematics 2024-08-13 Daniel Bienstock , Yury Dvorkin , Cheng Guo , Robert Mieth , Jiayi Wang

Traditional pricing paradigms, once dominated by static models and rule-based heuristics, are increasingly being replaced by dynamic, data-driven approaches powered by machine learning algorithms. Despite their growing sophistication, most…

Machine Learning · Computer Science 2025-12-01 Marco Mussi , Marcello Restelli

Electrification is contributing to substantial growth in U.S. commercial and industrial loads, but the cost and Scope 2 carbon emission implications of this load growth are opaque for both power consumers and utilities. This work describes…

Systems and Control · Electrical Eng. & Systems 2026-01-21 Fletcher T. Chapin , Akshay K. Rao , Adhithyan Sakthivelu , Carson I. Tucker , Eres David , Casey S. Chen , Erin Musabandesu , Meagan S. Mauter

The price movement prediction of stock market has been a classical yet challenging problem, with the attention of both economists and computer scientists. In recent years, graph neural network has significantly improved the prediction…

Statistical Finance · Quantitative Finance 2023-05-16 Sheng Xiang , Dawei Cheng , Chencheng Shang , Ying Zhang , Yuqi Liang

In the context of smart city transportation, efficient matching of taxi supply with passenger demand requires real-time integration of urban traffic network data and mobility patterns. Conventional taxi hotspot prediction models often rely…

Machine Learning · Computer Science 2026-01-05 Sonia Khetarpaul , P Y Sharan

Network Utility Maximization (NUM) studies the problems of allocating traffic rates to network users in order to maximize the users' total utility subject to network resource constraints. In this paper, we propose a new NUM framework,…

Networking and Internet Architecture · Computer Science 2020-12-18 Xinzhe Fu , Eytan Modiano

Line planning in public transport is the strategic problem of selecting lines and their operating frequencies. This problem is important as it defines the passenger service, based on available connections and expected travel times, and…

The advances in information and communication technology are changing theway people move. Companies that offer demand-responsive transportation serviceshave the opportunity to reduce their costs and increase their revenues…

Optimization and Control · Mathematics 2021-05-12 Enrico Angelelli , Valentina Morandi , Maria Grazia Speranza

This paper addresses developing cost-effective strategies to respond to excessive demand in the service network design problem in a multi-period setting. The common assumption states that the capacity of freight carriers' assets is capable…

Optimization and Control · Mathematics 2019-06-24 Yusuf Secerdin , Murat Erkoc

Mobile Collaborative Internet Access (MCA) enables mobile users to share their Internet through flexible tethering arrangements. This can potentially make better use of network resources. However, from a mobile network operator's (MNO's)…

Networking and Internet Architecture · Computer Science 2019-04-10 Meng Zhang , Lin Gao , Jianwei Huang , Michael L. Honig

In this paper, we study optimization problems where the cost function contains time-varying parameters that are unmeasurable and evolve according to linear, yet unknown, dynamics. We propose a solution that leverages control theoretic tools…

Optimization and Control · Mathematics 2025-03-20 Shivanshu Tripathi , Abed AlRahman Al Makdah , Fabio Pasqualetti

Ubiquitous mobile computing have enabled ride-hailing services to collect vast amounts of behavioral data of riders and drivers and optimize supply and demand matching in real time. While these mobility service providers have some degree of…

Machine Learning · Computer Science 2021-02-16 Takuma Oda

We consider the problem of optimal bidding for virtual trading in two-settlement electricity markets. A virtual trader aims to arbitrage on the differences between day-ahead and real-time market prices; both prices, however, are random and…

Computer Science and Game Theory · Computer Science 2018-08-02 Sevi Baltaoglu , Lang Tong , Qing Zhao

We study dynamic pricing where a seller repeatedly interacts with a strategic, non-myopic buyer who has a fixed private valuation and discounts future utility. Prior work focused exclusively on posted-price mechanisms, which only extract…

Computer Science and Game Theory · Computer Science 2026-04-28 Shiliang Zuo

Communication networks are time-varying and hence, fair sharing of network resources among the users in such a dynamic environment is a challenging task. In this context, a time-varying network model is designed and the shortest user's…

Networking and Internet Architecture · Computer Science 2019-05-10 Suchi Kumari , Anurag Singh

Demand response provides utilities with a mechanism to share with end users the stochasticity resulting from the use of renewable sources. Pricing is accordingly used to reflect energy availability, to allocate such a limited resource to…

Artificial Intelligence · Computer Science 2016-06-08 Andrea Monacchi , Wilfried Elmenreich

Prosumer operators are dealing with extensive challenges to participate in short-term electricity markets while taking uncertainties into account. Challenges such as variation in demand, solar energy, wind power, and electricity prices as…

Machine Learning · Computer Science 2022-03-14 Saeed Mohammadi , Mohammad Reza Hesamzadeh

Access to a large variety of data across a massive population has made it possible to predict customer purchase patterns and responses to marketing campaigns. In particular, accurate demand forecasts for popular products with frequent…

Machine Learning · Statistics 2019-01-01 Tianle Chen , Brian Keng , Javier Moreno