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About

I was born in Russia in the city called Irkutsk, located in the middle of Siberia. In 2006 I graduated from the Institute of Mathematics Economics and Informatics of Irkutsk State University with the Master Degree in Applied Mathematics. Then I had started my post-graduate study at the Institute of System Dynamics and Control Theory of Siberian Branch of the Russian Academy of Sciences, Irkutsk, where in December, 2010, I have successfully defended my PhD thesis in Operations Research. In November, 2011 I have moved to Portugal and joined the research activities at INESC Porto under the project on Kidney Exchange Programs. Currently I continue research within this application of operations research under FCT post-doc grant.

My research interests are in the field of combinatorial optimization: modelling, development the methods for solving the problems such as branch and cut and price methods, cutting plane methods, column generation. As to applications I have worked on kidney exchange problem, location problems, clustering problem, PMU placement problem.

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Publications

2022

The Probabilistic Travelling Salesman Problem with Crowdsourcing

Authors
Santini, A; Viana, A; Klimentova, X; Pedroso, JP;

Publication
COMPUTERS & OPERATIONS RESEARCH

Abstract
We study a variant of the Probabilistic Travelling Salesman Problem arising when retailers crowdsource last-mile deliveries to their own customers, who can refuse or accept in exchange for a reward. A planner must identify which deliveries to offer, knowing that all deliveries need fulfilment, either via crowdsourcing or using the retailer's own vehicle. We formalise the problem and position it in both the literature about crowdsourcing and among routing problems in which not all customers need a visit. We show that to evaluate the objective function of this stochastic problem for even one solution, one needs to solve an exponential number of Travelling Salesman Problems. To address this complexity, we propose Machine Learning and Monte Carlo simulation methods to approximate the objective function, and both a branch-and-bound algorithm and heuristics to reduce the number of evaluations. We show that these approaches work well on small size instances and derive managerial insights on the economic and environmental benefits of crowdsourcing to customers.

2021

Robust Models for the Kidney Exchange Problem

Authors
Carvalho, M; Klimentova, X; Glorie, K; Viana, A; Constantino, M;

Publication
INFORMS JOURNAL ON COMPUTING

Abstract
Scope and Mission

2021

Fairness models for multi-agent kidney exchange programmes

Authors
Klimentova, X; Viana, A; Pedroso, JP; Santos, N;

Publication
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE

Abstract
Nowadays there are several countries running independent kidney exchange programmes (KEPs). These programmes allow a patient with kidney failure, having a willing healthy but incompatible donor, to receive a transplant from a similar pair where the donor is compatible with him. Since in general larger patient-donor pools allow for more patients to be matched, this prompts independent programmes (agents) to merge their pools and collaborate in order to increase the overall number of transplants. Such collaboration does however raise a problem: how to assign transplants to agents so that there is a balance between the contribution each agent brings to the merged pool and the benefit it gets from the collaboration. In this paper we propose a new Integer Programming model for multi-agent kidney exchange programmes (mKEPs). It considers the possible existence of multiple optimal solutions in each matching period of a KEP and, in consecutive matching periods, selects the optimal solution among the set of alternative ones in such a way that in the long-term the benefit each agent gets from participating in the mKEP is balanced accordingly to a given criterion. This is done by use of a memory mechanism. Extensive computational tests show the benefit of mKEPs, when compared to independent KEPs, in terms of potential increase in the number of transplants. Furthermore, they show that, under different policies, the number of additional transplants each agent receives can vary significantly. More importantly, results show that the proposed methodology consistently obtains more stable results than methodologies that do not use memory. © 2020 Elsevier Ltd

2021

Modelling and optimisation in European Kidney Exchange Programmes

Authors
Biro, P; van de Klundert, J; Manlove, D; Pettersson, W; Andersson, T; Burnapp, L; Chromy, P; Delgado, P; Dworczak, P; Haase, B; Hemke, A; Johnson, R; Klimentova, X; Kuypers, D; Costa, AN; Smeulders, B; Spieksma, F; Valentin, MO; Viana, A;

Publication
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH

Abstract
The complex multi-criteria optimisation problems arising in Kidney Exchange Programmes have received considerable attention both in practice and in the scientific literature. Whereas theoretical advancements are well reviewed and synthesised, this is not the case for practice. We present a synthesis of models and methods applied in present European Kidney Exchange Programmes, which is based on detailed descriptions we created for this purpose. Most descriptions address national programmes, yet we also present findings on emerging cross-national programmes. The synthesis provides a systematic and detailed description of the models and methods the programmes use, revealing important commonalities as well as considerable variation among them. Rather than distilling a single best practice from these results, we find that the variation in models and methods arises because of variation in country characteristics, policies, and ethics. The synthesised state of the art may benefit future national and cross-national initiatives and direct future theoretical contributions within and across the boundaries of the Operations Research discipline. © 2019

2020

Compensation Scheme With Shapley Value For Multi-Country Kidney Exchange Programmes

Authors
Biro, P; Gyetvai, M; Klimentova, X; Pedroso, JP; Pettersson, W; Viana, A;

Publication
ECMS 2020 Proceedings edited by Mike Steglich, Christian Mueller, Gaby Neumann, Mathias Walther

Abstract