Imperial College London


Faculty of EngineeringDepartment of Civil and Environmental Engineering

Research Associate







222Skempton BuildingSouth Kensington Campus





Publication Type

10 results found

Anastasiadis E, Angeloudis P, Ainalis D, Ye Q, Hsu P-Y, Karamanis R, Escribano J, Stettler Met al., 2020, On the selection of charging facility locations for EV-based ride-hailing services: A computational case study, Sustainability, ISSN: 2071-1050

Journal article

Karamanis R, Anastasiadis E, Stettler M, Angeloudis Pet al., 2020, Vehicle redistribution in ride-sourcing markets using convex minimum cost flows, Publisher: arXiv

Ride-sourcing platforms often face imbalances in the demand and supply ofrides across areas in their operating road-networks. As such, dynamic pricingmethods have been used to mediate these demand asymmetries through surge pricemultipliers, thus incentivising higher driver participation in the market.However, the anticipated commercialisation of autonomous vehicles couldtransform the current ride-sourcing platforms to fleet operators. The absenceof human drivers fosters the need for empty vehicle management to address anyvehicle supply deficiencies. Proactive redistribution using integer programmingand demand predictive models have been proposed in research to address thisproblem. A shortcoming of existing models, however, is that they ignore themarket structure and underlying customer choice behaviour. As such, currentmodels do not capture the real value of redistribution. To resolve this, weformulate the vehicle redistribution problem as a non-linear minimum cost flowproblem which accounts for the relationship of supply and demand of rides, byassuming a customer discrete choice model and a market structure. Wedemonstrate that this model can have a convex domain, and we introduce an edgesplitting algorithm to solve a transformed convex minimum cost flow problem forvehicle redistribution. By testing our model using simulation, we show that ourredistribution algorithm can decrease wait times up to 50% and increase vehicleutilization up to 8%. Our findings outline that the value of redistribution iscontingent on localised market structure and customer behaviour.

Working paper

Karamanis R, Anastasiadis E, Angeloudis P, Stettler Met al., 2020, Assignment and pricing of shared rides in ride-sourcing using combinatorial double auctions, IEEE Transactions on Intelligent Transportation Systems, ISSN: 1524-9050

Transportation Network Companies employ dynamic pricing methods at periods of peak travel to incentivise driver participation and balance supply and demand for rides. Surge pricing multipliers are commonly used and are applied following demand and estimates of customer and driver trip valuations. Combinatorial double auctions have been identified as a suitable alternative, as they can achieve maximum social welfare in the allocation by relying on customers and drivers stating their valuations. A shortcoming of current models, however, is that they fail to account for the effects of trip detours that take place in shared trips and their impact on the accuracy of pricing estimates. To resolve this, we formulate a new shared-ride assignment and pricing algorithm using combinatorial double auctions. We demonstrate that this model is reduced to a maximum weighted independent set model, which is known to be APX-hard. A fast local search heuristic is also presented, which is capable of producing results that lie within 10% of the exact approach for practical implementations. Our proposed algorithm could be used as a fast and reliable assignment and pricing mechanism of ride-sharing requests to vehicles during peak travel times.

Journal article

Anastasiadis E, Deligkas A, 2020, Heterogeneous Facility Location Games., CoRR, Vol: abs/2005.03095

Journal article

Pitropakis N, Panaousis E, Giannetsos T, Anastasiadis E, Loukas Get al., 2019, A taxonomy and survey of attacks against machine learning, COMPUTER SCIENCE REVIEW, Vol: 34, ISSN: 1574-0137

Journal article

Anastasiadis E, Deng X, Krysta P, Li M, Qiao H, Zhang Jet al., 2019, Network Pollution Games, ALGORITHMICA, Vol: 81, Pages: 124-166, ISSN: 0178-4617

Journal article

Anastasiadis E, Deligkas A, 2018, Heterogeneous Facility Location Games., AAMAS 2018, Publisher: International Foundation for Autonomous Agents and Multiagent Systems Richland, SC, USA / ACM, Pages: 623-631

Conference paper

Kandris D, Tselikis G, Anastasiadis E, Panaousis E, Dagiuklas Tet al., 2017, COALA: A Protocol for the Avoidance and Alleviation of Congestion in Wireless Sensor Networks, SENSORS, Vol: 17, ISSN: 1424-8220

Journal article

Anastasiadis E, Deng X, Krysta P, Li M, Qiao H, Zhang Jet al., 2016, New Results for Network Pollution Games, 22nd International Computing and Combinatorics Conference (COCOON), Publisher: SPRINGER INTERNATIONAL PUBLISHING AG, Pages: 39-51, ISSN: 0302-9743

Conference paper

Anastasiadis E, Deng X, Krysta P, Li M, Qiao H, Zhang Jet al., 2016, Network Pollution Games, 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Publisher: ASSOC COMPUTING MACHINERY, Pages: 23-31

Conference paper

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