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Computer Science, Information Systems
Oliver Gebhard, Max Hahn-Klimroth, Olaf Parczyk, Manuel Penschuck, Maurice Rolvien, Jonathan Scarlett, Nelvin Tan
Summary: This paper presents recent advances in noiseless non-adaptive group testing, closing the gaps between achievability and converse bounds for the required number of tests under practical constraints. Optimal algorithms are provided for Delta-divisible items and Gamma-sized tests, and gaps between the performance of adaptive and non-adaptive algorithms are demonstrated.
IEEE TRANSACTIONS ON INFORMATION THEORY
(2022)
Article
Management
Sebastian Perez-Salazar, Ishai Menache, Mohit Singh, Alejandro Toriello
Summary: Cloud computing has brought renewed interest in resource allocation problems, with constraints such as SLAs. A simple and effective algorithm has been proposed to achieve high utilization of resources and simultaneously satisfy all individual SLAs with minimal error.
OPERATIONS RESEARCH
(2021)
Article
Business
Daniel Nunan, MariaLaura Di Domenico
Summary: The choice of pricing strategy is crucial for value creation and market functioning. Technological advancements and abundant data enable more innovative pricing strategies. However, there is a lack of understanding about the specific challenges brought by algorithmically generated dynamic pricing in the emerging literature on pricing ethics. This paper expands the current understanding of pricing ethics by conceptualizing the ethical challenges of contemporary dynamic pricing, and proposes a governance model that considers the role of customers as stakeholders in value creation.
JOURNAL OF BUSINESS RESEARCH
(2022)
Article
Management
Will Ma, David Simchi-Levi, Jinglong Zhao
Summary: This study investigates the efficacy of static control policies in revenue management problems for a large consumer packaged goods company. The results show that simple static policies can approximate the optimal solution, especially with large initial inventories. The adaptation of prophet inequalities from optimal stopping theory to pricing and assortment problems is effective in addressing dynamic demand and allocation challenges.
MANAGEMENT SCIENCE
(2021)
Article
Economics
Aldric Vives, Marta Jacob
Summary: This study demonstrates the importance of implementing personalized pricing policies during high season to maximize hotel revenue, despite the common practice of hotel companies using similar pricing strategies for hotels in the same destination. The deterministic model performed well with data from seven different hotels with varied customer profiles and characteristics, highlighting the potential for revenue management improvements in the hotel industry.
Article
Computer Science, Artificial Intelligence
Shangdong Yang, Yang Gao
Summary: This study focuses on a variation of the stochastic multiarmed bandit (MAB) problems, where the agent knows the a priori knowledge called the near-optimal mean reward (NoMR). By utilizing NoMR, a novel algorithm called NOMR-BANDIT is proposed to optimize algorithm performance. The upper and lower bounds of regret in NOMR-BANDIT are uniform, making it an optimal algorithm for this problem.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2021)
Article
Management
Boxiao Chen, Yining Wang, Yuan Zhou
Summary: This study investigates the classic model of joint pricing and inventory control with lost sales and develops nonparametric online learning algorithms to achieve the optimal policy. It proposes a novel inversion method and search methods to control regrets for concave and non-concave reward functions. In addition, it offers a lower bound based on generalized Hellinger distance through information-theoretical argument.
MANAGEMENT SCIENCE
(2023)
Article
Computer Science, Information Systems
Shiji Zhou, Zhi Wang, Chenghao Hu, Yinan Mao, Haopeng Yan, Shanghang Zhang, Chuan Wu, Wenwu Zhu
Summary: This paper introduces an online caching policy for dynamic environments where popularity is highly dynamic and cannot be modeled using regular stochastic patterns. The policy achieves reduced user access latency and faster content downloads through an online optimization framework and dynamic online learning method.
IEEE TRANSACTIONS ON MULTIMEDIA
(2023)
Article
Computer Science, Theory & Methods
Jianzhen Luo, Jun Li, Lei Jiao, Jun Cai
Summary: This article introduces an algorithm to convert original SFC into parallelized SFC and proposes a heuristic method, ParaSFC, for deploying multiple p-SFCs over the network to serve a large number of users. By parallelizing the processing, ParaSFC reduces the average service latency of all deployed p-SFCs and offers better resource utilization.
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
(2021)
Article
Management
Xinru Hu, Shuiyin Zhou, Xiaomeng Luo, Jianbin Li, Chi Zhang
Summary: This paper focuses on the pricing strategy of online ride-hailing platforms, specifically discussing surge pricing and bonus incentive strategies. The study finds that these strategies have different effects under different conditions, and overall, bonus incentive strategy improves social welfare better.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2024)
Article
Statistics & Probability
Wenlong Mou, Nicolas Flammarion, Martin J. Wainwright, Peter L. Bartlett
Summary: In this study, we propose an improved non-asymptotic analysis for the Euler-Maruyama discretization of the Langevin diffusion. Compared to existing approaches, our analysis does not require global contractivity and has polynomial time complexity. We also improve the rate of the discretization step size in terms of the KL divergence from O(eta) to O(eta 2). This result matches the correct order for numerical SDEs without exponential time dependence and can simultaneously improve the analysis of various sampling algorithms based on Dalalyan's approach when applied to MCMC.
Article
Engineering, Industrial
Rainer Schlosser, Regis Y. Chenavaz, Stanko Dimitrov
Summary: This study develops an optimal control model that integrates a firm's recycling rate to determine optimal recycling and pricing policies. The research demonstrates how jointly optimized controls can be dynamically adjusted to achieve sustainability in the production process. Numerical experiments are used to assess the existence of a steady-state and calculate sensitivity analyses with respect to various model parameters.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2021)
Article
Management
Amine Allouah, Achraf Bahamou, Omar Besbes
Summary: This article studies how to price based on historical data, evaluates the value of such data, and provides a framework to optimize pricing policies and algorithms to adapt to different sales probabilities. For example, if half of the customers purchase the product at the historical price, it is possible to guarantee 85% of the theoretical optimal performance; even if only 1% of the customers purchase, it is still possible to guarantee 51% of the theoretical optimal performance.
MANAGEMENT SCIENCE
(2023)
Article
Computer Science, Theory & Methods
Sayan Bhattacharya, Monika Henzinger, Danupon Nanongkai, Xiaowei Wu
Summary: This research addresses the dynamic minimum set cover problem and achieves near-optimal approximations using deterministic algorithms in the low-frequency range. The algorithms provide different guarantees on the update time and improve upon previous results, offering better bounds on the update time for various scenarios.
SIAM JOURNAL ON COMPUTING
(2023)
Article
Computer Science, Interdisciplinary Applications
Yu-Chung Tsao, Tsehaye Dedimas Beyene, Vo-Van Thanh, Sisay G. Gebeyehu
Summary: This study considers the establishment of a power distribution network design with distributed renewable energy resources and the involvement of prosumers in the energy system. By developing a mathematical model and solution approach, the study determines the generation capacity of distributed renewable energy resources, differential prices, and buy-back price while maximizing the profit of a power plant. The results show that offering a high buy-back price to incentivize prosumers can lead to the highest profit.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Management
Omar Besbes, Ilan Lobel
MANAGEMENT SCIENCE
(2015)
Article
Management
Santiago R. Balseiro, Omar Besbes, Gabriel Y. Weintraub
MANAGEMENT SCIENCE
(2015)
Article
Management
Omar Besbes, Assaf Zeevi
MANAGEMENT SCIENCE
(2015)
Article
Management
Omar Besbes, Yonatan Gur, Assaf Zeevi
M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT
(2016)
Article
Management
Omar Besbes, Dan A. Iancu, Nikolaos Trichakis
MANAGEMENT SCIENCE
(2018)
Article
Management
Tian Heong Chan, Francis de Vericourt, Omar Besbes
MANAGEMENT SCIENCE
(2019)
Article
Management
Omar Besbes, Marco Scarsini
OPERATIONS RESEARCH
(2018)
Article
Management
Santiago R. Balseiro, Omar Besbes, Gabriel Y. Weintraub
OPERATIONS RESEARCH
(2019)
Article
Management
Amine Allouah, Omar Besbes
MANAGEMENT SCIENCE
(2020)
Article
Management
Omar Besbes, Adam N. Elmachtoub, Yunjie Sun
INFORMS JOURNAL ON APPLIED ANALYTICS
(2020)
Article
Management
Omar Besbes, Francisco Castro, Ilan Lobel
Summary: We studied the pricing problem of a platform matching price-sensitive customers and flexible supply units within a geographic area, proposing a two-dimensional framework and elucidating structural properties of supply equilibria. By establishing a suitable knapsack structure, we were able to provide a crisp local characterization of optimal prices and supply response. The optimal solution involves different treatments for different locations and induces movement away from demand shocks.
MANAGEMENT SCIENCE
(2021)
Article
Management
Omar Besbes, N. Adam Elmachtoub, Yunjie Sun
Summary: The study examines a fundamental pricing model for various markets of reusable resources. It analyzes the performance of static pricing in maximizing profit, market share, and service level, providing insights on how a static pricing policy can come close to optimal results under certain conditions.
OPERATIONS RESEARCH
(2022)
Article
Management
Raghav Singal, Omar Besbes, Antoine Desir, Vineet Goyal, Garud Iyengar
Summary: One of the central challenges in online advertising is attribution. This paper proposes an axiomatic framework and a novel metric called CASV to address the attribution problem. The authors compare CASV with commonly used metrics using a Markovian model.
MANAGEMENT SCIENCE
(2022)
Article
Management
Amine Allouah, Achraf Bahamou, Omar Besbes
Summary: This paper examines the data-driven pricing problem of determining optimal pricing based on a limited number of samples from customer value distribution. The study focuses on achievable performance for regular and monotone hazard rate distributions, developing a unified general approach to quantify mechanism performance and analyze new policies with increasing samples. Insights on the value of samples for pricing purposes are uncovered, highlighting the impact of sample size on achieving performance goals.
OPERATIONS RESEARCH
(2022)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Santiago R. Balseiro, Omar Besbes, Gabriel Y. Weintraub
EC'16: PROCEEDINGS OF THE 2016 ACM CONFERENCE ON ECONOMICS AND COMPUTATION
(2016)