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Publications

Publications by Ana Viana

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).

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.

2014

A MILP-Based Approach for Hydrothermal Scheduling

Authors
Rahman, DF; Viana, A; Pedroso, JP;

Publication
OPERATIONS RESEARCH PROCEEDINGS 2012

Abstract

2014

Metaheuristic search based methods for unit commitment

Authors
Rahman, DF; Viana, A; Pedroso, JP;

Publication
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS

Abstract
This paper presents two new solution approaches capable of finding optimal solutions for the thermal unit commitment problem in power generation planning. The approaches explore the concept of "matheuristics", a term usually used to refer to an optimization algorithm that hybridizes (meta)heuristics with mixed integer programming solvers, in order to speed up convergence to optimality for large scale instances. Two algorithms are proposed: "local branching", and an hybridization of particle swarm optimization with a mixed integer programming solver. From extensive computational tests on a broad set of benchmarks, the algorithms were found to be able to solve large instances. Optimal solutions were obtained for several well-known situations with dramatic reductions in CPU time for the larger cases, when compared to previously proposed exact methods.

2014

A New Branch-and-Price Approach for the Kidney Exchange Problem

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

Publication
COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2014, PT II

Abstract
The kidney exchange problem (KEP) is an optimization problem arising in the framework of transplant programs that allow exchange of kidneys between two or more incompatible patient-donor pairs. In this paper an approach based on a new decomposition model and branch-and-price is proposed to solve large KEP instances. The optimization problem considers, hierarchically, the maximization of the number of transplants and the minimization of the size of exchange cycles. Computational comparison of different variants of branch-and-price for the standard and the proposed objective functions are presented. The results show the efficiency of the proposed approach for solving large instances.

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