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20112022
most citedNonhomogeneous Place-Dependent Markov Chains, Unsynchronised AIMD, and Network Utility Maximization

15 citations · 83 across the 22 of their papers we have counts for

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9 papers · 1 filter

math.OC2021

Multi-resource allocation for federated settings: A non-homogeneous Markov chain model

Syed Eqbal Alam, Fabian Wirth, Jia Yuan Yu

In a federated setting, agents coordinate with a central agent or a server to solve an optimization problem in which agents do not share their information with each other. Wirth an…

math.OC2020

The Convergence of Finite-Averaging of AIMD for Distributed Heterogeneous Resource Allocations

Syed Eqbal Alam, Fabian Wirth, Jia Yuan Yu +1

In several social choice problems, agents collectively make decisions over the allocation of multiple divisible and heterogeneous resources with capacity constraints to maximize ut…

math.OC2017

Distributionally Robust Optimisation in Congestion Control

Jakub Marecek, Robert Shorten, Jia Yuan Yu

The effects of real-time provision of travel-time information on the behaviour of drivers are considered. The model of Marecek et al. [arXiv:1406.7639, Int. J. Control 88(10), 2015…

math.OC2016★ 8 cited

Pricing Vehicle Sharing with Proximity Information

Jakub Marecek, Robert Shorten, Jia Yuan Yu

For vehicle sharing schemes, where drop-off positions are not fixed, we propose a pricing scheme, where the price depends in part on the distance between where a vehicle is being d…

math.OC2015

A Fair Assignment of Drivers to Parking Lots

Nicole Taheri, Jia Yuan Yu, Robert Shorten

Searching for a parking spot can waste time and gasoline. This waste can be reduced by assigning drivers to parking lots based on their destination and arrival time. In such a syst…

math.OC2015★ 2 cited

On the Design of Campus Parking Systems with QoS guarantees

Wynita Griggs, Jia Yuan Yu, Fabian Wirth +2

Parking spaces are resources that can be pooled together and shared, especially when there are complementary day-time and night-time users. We answer two design questions. First, g…