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This paper studies an online selection problem, where a seller seeks to sequentially sell multiple copies of an item to arriving buyers. We consider an adversarial setting, making no modeling assumptions about buyers' valuations for the…

Computer Science and Game Theory · Computer Science 2024-10-11 Bo Sun , Hossein Nekouyan Jazi , Xiaoqi Tan , Raouf Boutaba

Buying and selling of data online has increased substantially over the last few years. Several frameworks have already been proposed that study query pricing in theory and practice. The key guiding principle in these works is the notion of…

Databases · Computer Science 2019-09-10 Shuchi Chawla , Shaleen Deep , Paraschos Koutris , Yifeng Teng

The high proportions of demand charges in electric bills motivate large-power customers to leverage energy storage for reducing the peak procurement from the outer grid. Given limited energy storage, we expect to maximize the peak-demand…

Systems and Control · Electrical Eng. & Systems 2021-08-25 Yanfang Mo , Qiulin Lin , Minghua Chen , Si-Zhao Joe Qin

We consider an online two-stage stochastic optimization with long-term constraints over a finite horizon of $T$ periods. At each period, we take the first-stage action, observe a model parameter realization and then take the second-stage…

Machine Learning · Computer Science 2024-01-03 Piao Hu , Jiashuo Jiang , Guodong Lyu , Hao Su

We study a game-theoretic variant of the maximum circulation problem. In a flow allocation game, we are given a directed flow network. Each node is a rational agent and can strategically allocate any incoming flow to the outgoing edges.…

Computer Science and Game Theory · Computer Science 2023-12-22 Nils Bertschinger , Martin Hoefer , Daniel Schmand

We formulate selecting the best optimizing system (SBOS) problems and provide solutions for those problems. In an SBOS problem, a finite number of systems are contenders. Inside each system, a continuous decision variable affects the…

Methodology · Statistics 2025-11-04 Nian Si , Yifu Tang , Zeyu Zheng

Reinforcement learning has been explored for many problems, from video games with deterministic environments to portfolio and operations management in which scenarios are stochastic; however, there have been few attempts to test these…

General Finance · Quantitative Finance 2024-02-19 Sherly Alfonso-Sánchez , Jesús Solano , Alejandro Correa-Bahnsen , Kristina P. Sendova , Cristián Bravo

This paper studies an online optimal resource reservation problem in communication networks with job transfers where the goal is to minimize the reservation cost while maintaining the blocking cost under a certain budget limit. To tackle…

Optimization and Control · Mathematics 2024-05-07 Ahmed Sid-Ali , Ioannis Lambadaris , Yiqiang Q. Zhao , Gennady Shaikhet , Amirhossein Asgharnia

In the online sorting problem, we have an array $A$ of $n$ cells, and receive a stream of $n$ items $x_1,\dots,x_n\in [0,1]$. When an item arrives, we need to immediately and irrevocably place it into an empty cell. The goal is to minimize…

Data Structures and Algorithms · Computer Science 2025-10-23 Yang Hu

We consider an assortment optimization problem where a customer chooses a single item from a sequence of sets shown to her, while limited inventories constrain the items offered to customers over time. In the special case where all of the…

Data Structures and Algorithms · Computer Science 2020-07-28 Elaheh Fata , Will Ma , David Simchi-Levi

Fantasy football leagues involve strategic player trades to optimize team performance. However, identifying optimal trades is complex due to varying player projections, positional needs, and league-specific scoring. Existing approaches…

Neural and Evolutionary Computing · Computer Science 2025-11-25 Evan Parshall , Junaid Ali , Michael Zimmerman

We propose stochastic rank-$1$ bandits, a class of online learning problems where at each step a learning agent chooses a pair of row and column arms, and receives the product of their values as a reward. The main challenge of the problem…

Machine Learning · Computer Science 2017-03-09 Sumeet Katariya , Branislav Kveton , Csaba Szepesvari , Claire Vernade , Zheng Wen

We consider an online vector balancing game where vectors $v_t$, chosen uniformly at random in $\{-1,+1\}^n$, arrive over time and a sign $x_t \in \{-1,+1\}$ must be picked immediately upon the arrival of $v_t$. The goal is to minimize the…

Data Structures and Algorithms · Computer Science 2020-07-14 Nikhil Bansal , Joel H. Spencer

In this paper we consider multiple constrained resource allocation problems, where the constraints can be specified by formulating activity dependency restrictions or by using game-theoretic models. All the problems are focused on generic…

Data Structures and Algorithms · Computer Science 2009-06-19 Mugurel Ionut Andreica , Madalina Ecaterina Andreica , Costel Visan

We study a multi-objective model on the allocation of reusable resources under model uncertainty. Heterogeneous customers arrive sequentially according to a latent stochastic process, request for certain amounts of resources, and occupy…

Optimization and Control · Mathematics 2023-08-02 Xilin Zhang , Wang Chi Cheung

This paper is devoted to the online dominating set problem and its variants. We believe the paper represents the first systematic study of the effect of two limitations of online algorithms: making irrevocable decisions while not knowing…

Data Structures and Algorithms · Computer Science 2018-09-14 Joan Boyar , Stephan J. Eidenbenz , Lene M. Favrholdt , Michal Kotrbčík , Kim S. Larsen

Numerous combinatorial optimization problems (knapsack, maximum-weight matching, etc.) can be expressed as \emph{subset maximization problems}: One is given a ground set $N=\{1,\dots,n\}$, a collection $\mathcal{F}\subseteq 2^N$ of subsets…

Data Structures and Algorithms · Computer Science 2019-05-13 Evripidis Bampis , Bruno Escoffier , Kevin Schewior , Alexandre Teiller

We consider a two-way trading problem, where investors buy and sell a stock whose price moves within a certain range. Naturally they want to maximize their profit. Investors can perform up to $k$ trades, where each trade must involve the…

Data Structures and Algorithms · Computer Science 2017-06-19 Stanley P. Y. Fung

Aiming to overcome some of the limitations of worst-case analysis, the recently proposed framework of "algorithms with predictions" allows algorithms to be augmented with a (possibly erroneous) machine-learned prediction that they can use…

Computer Science and Game Theory · Computer Science 2024-03-28 Eric Balkanski , Vasilis Gkatzelis , Xizhi Tan , Cherlin Zhu

We study coalition formation in the framework of fractional hedonic games (FHGs). The objective is to maximize social welfare in an online model where agents arrive one by one and must be assigned to coalitions immediately and irrevocably.…

Computer Science and Game Theory · Computer Science 2025-10-22 Martin Bullinger , René Romen , Alexander Schlenga
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