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About

About

Ana Viana holds a PhD in Electrical and Computers Engineering (University of Porto, 2004).

She is Head of the Centre for Industrial Engineering and Management of INESC TEC and Coordinator Professor at the Polytechnic of Porto, School of Engineering.

Her research interests focus on Combinatorial Optimisation, both on the development of exact and (meta-)heuristics approaches.

She led several research projects with public funding and publishes regularly in reference scientific journals of her area of activity.

Interest
Topics
Details

Details

006
Publications

2017

Nash equilibria in the two-player kidney exchange game

Authors
Carvalho, M; Lodi, A; Pedroso, JP; Viana, A;

Publication
MATHEMATICAL PROGRAMMING

Abstract
Kidney exchange programs have been set in several countries within national, regional or hospital frameworks, to increase the possibility of kidney patients being transplanted. For the case of hospital programs, it has been claimed that hospitals would benefit if they collaborated with each other, sharing their internal pools and allowing transplants involving patients of different hospitals. This claim led to the study of multi-hospital exchange markets. We propose a novel direction in this setting by modeling the exchange market as an integer programming game. The analysis of the strategic behavior of the entities participating in the kidney exchange game allowed us to prove that the most rational game outcome maximizes the social welfare and that it can be computed in polynomial time.

2016

A multiple criteria utility-based approach for unit commitment with wind power and pumped storage hydro

Authors
Vieira, B; Viana, A; Matos, M; Pedroso, JP;

Publication
ELECTRIC POWER SYSTEMS RESEARCH

Abstract
The integration of wind power in electricity generation brings new challenges to the unit commitment problem, as a result of the random nature of the wind speed. The scheduling of thermal generation units at the day-ahead stage is usually based on wind power forecasts. Due to technical limitations of thermal units, deviations from those forecasts during intra-day operations may lead to unwanted consequences, such as load shedding and increased operating costs. Wind power forecasting uncertainty has been handled in practice by means of conservative stochastic scenario-based optimization models, or through additional operating reserve settings. However, generation companies may have different attitudes towards the risks associated to wind power variability. In this paper, operating costs and load shedding are modeled by non-linear utility functions aggregated into a single additive utility function of a multi-objective model. Computational experiments have been done to validate the approach: firstly we test our model for the wind-thermal unit commitment problem and, in a second stage, pumped storage hydro units are added, leading to a model with wind-hydro-thermal coordination. Results have shown that the proposed methodology is able to correctly reflect different risk profiles of decision makers for both models.

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.

2013

A new MILP-based approach for unit commitment in power production planning

Authors
Viana, A; Pedroso, JP;

Publication
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS

Abstract
s This paper presents a complete, quadratic programming formulation of the standard thermal unit commitment problem in power generation planning, together with a novel iterative optimisation algorithm for its solution. The algorithm, based on a mixed-integer formulation of the problem, considers piecewise linear approximations of the quadratic fuel cost function that are dynamically updated in an iterative way, converging to the optimum: this avoids the requirement of resorting to quadratic programming, making the solution process much quicker. From extensive computational tests on a broad set of benchmark instances of this problem, the algorithm was found to be flexible and capable of easily incorporating different problem constraints. Indeed, it is able to tackle ramp constraints, which although very important in practice were rarely considered in previous publications. Most importantly, optimal solutions were obtained for several well-known benchmark instances. including instances of practical relevance, that are not yet known to have been solved to optimality. Computational experiments and their results showed that the method proposed is both simple and extremely effective.

2013

New insights on integer-programming models for the kidney exchange problem

Authors
Constantino, M; Klimentova, X; Viana, A; Rais, A;

Publication
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH

Abstract
In recent years several countries have set up policies that allow exchange of kidneys between two or more incompatible patient-donor pairs. These policies lead to what is commonly known as kidney exchange programs. The underlying optimization problems can be formulated as integer programming models. Previously proposed models for kidney exchange programs have exponential numbers of constraints or variables, which makes them fairly difficult to solve when the problem size is large. In this work we propose two compact formulations for the problem, explain how these formulations can be adapted to address some problem variants, and provide results on the dominance of some models over others. Finally we present a systematic comparison between our models and two previously proposed ones via thorough computational analysis. Results show that compact formulations have advantages over non-compact ones when the problem size is large.

Supervised
thesis

2017

Otimização do posicionamento de PMUs numa rede elétrica

Author
TIAGO RAFAEL PINTO MONTEIRO

Institution
IPP-ISEP

2015

Desenvolvimento de Sequenciador para um Problema de Roteamento de Veículos

Author
HÉLDER FILIPE DE CASTRO PINHEIRO

Institution
IPP-ISEP

2015

Escalonamento de máquinas de cogeração utilizando programação inteira mista

Author
FÁBIO ONOFRE DA SILVA OLIVEIRA

Institution
IPP-ISEP

2015

Balancing and lot-sizing mixed-model lines in the footwear industry

Author
PARISA SADEGHI

Institution
IPP-ISEP