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About

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

2018

Observability of power systems with optimal PMU placement

Authors
Carvalho, M; Klimentova, X; Viana, A;

Publication
Computers & Operations Research

Abstract

2016

Maximising expectation of the number of transplants in kidney exchange programmes

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

Publication
Computers & OR

Abstract
This paper addresses the problem of maximising the expected number of transplants in kidney exchange programmes. New schemes for matching rearrangement in case of failure are presented, along with a new tree search algorithm used for the computation of optimal expected values. Extensive computational experiments demonstrate the effectiveness of the algorithm and reveal a clear superiority of a newly proposed scheme, subset-recourse, as compared to previously known approaches.

2016

Maximizing expected number of transplants in kidney exchange programs

Authors
Alvelos, F; Klimentova, X; Rais, A; Viana, A;

Publication
Electronic Notes in Discrete Mathematics

Abstract
In this paper we address the problem of maximizing the expected number of transplants in a kidney exchange program. We propose an integer programming model with an exponential number of decision variables which are associated with cycles. By introducing the concept of type of cycle, we avoid the complete cycle enumeration and develop a branch-and-price approach. © 2016 Elsevier B.V.

2016

Bi-level and Bi-objective p-Median Type Problems for Integrative Clustering: Application to Analysis of Cancer Gene-Expression and Drug-Response Data

Authors
Ushakov, AV; Klimentova, X; Vasilyev, I;

Publication
IEEE/ACM Transactions on Computational Biology and Bioinformatics

Abstract

2015

A compact formulation for maximizing the expected number of transplants in kidney exchange programs

Authors
Alvelos, F; Klimentova, X; Rais, A; Viana, A;

Publication
MINI EURO CONFERENCE ON IMPROVING HEALTHCARE: NEW CHALLENGES, NEW APPROACHES

Abstract
Kidney exchange programs (KEPs) allow the exchange of kidneys between incompatible donor-recipient pairs. Optimization approaches can help KEPs in defining which transplants should be made among all incompatible pairs according to some objective. The most common objective is to maximize the number of transplants. In this paper, we propose an integer programming model which addresses the objective of maximizing the expected number of transplants, given that there are equal probabilities of failure associated with vertices and arcs. The model is compact, i.e. has a polynomial number of decision variables and constraints, and therefore can be solved directly by a general purpose integer programming solver (e.g. Cplex).