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Sobre
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Sobre

Sou professora auxiliar com agregação da Faculdade de Economia da Universidade do Porto (FEP) e membro da direção do LIAAD, Laboratório de Inteligência Artificial e de Apoio à Decisão da UP. O LIAAD é um centro do INESC TEC desde 2007. Sou doutora em Management Science pelo Imperial College of London – Business School, mestre em Investigação Operacional pela The London School of Economics and Political Sciences e Licenciada em Engenharia Eletrotécnica e de Computadores pela Faculdade de Engenharia da Universidade do Porto. Fui professora visitante na University of Florida - Department of Industrial and Systems Engineering (2007/08) e na Texas A&M University – Department Industrial & Systems Engineering (2015-16).

Os meus interesses de investigação centram-se no desenvolvimento e aplicação de técnicas de Investigação Operacional e Inteligência Artificial para auxiliar a tomada de decisão em problemas de gestão em vários domínios (serviços, indústria, logística e transportes), com enfoque em problemas de otimização combinatória.

Na FEP leciono, essencialmente em Inglês, disciplinas de Investigação Operacional e Gestão das Operações ao primeiro ciclo, Logística, Análise de Decisão e Otimização aos segundo e terceiros ciclos e estou em vários Órgãos (Conselho de Representantes, Conselho Científico e Direção do Doutoramento em Gestão, entre outros).

Tópicos
de interesse
Detalhes

Detalhes

  • Nome

    Dalila Fontes
  • Cluster

    Informática
  • Cargo

    Investigador Sénior
  • Desde

    01 janeiro 2011
003
Publicações

2020

A Lagrangian Bound on the Clique Number and an Exact Algorithm for the Maximum Edge Weight Clique Problem

Autores
Hosseinian, S; Fontes, DBMM; Butenko, S;

Publicação
INFORMS Journal on Computing

Abstract

2020

Layout optimization of an airborne wind energy farm for maximum power generation

Autores
Roque, LAC; Paiva, LT; Fernandes, MCRM; Fontes, DBMM; Fontes, FACC;

Publicação
Energy Reports

Abstract
We consider a farm of Kite Power Systems (KPS) in the field of Airborne Wind Energy (AWE), in which each kite is connected to an electric ground generator by a tether. In particular, we address the problem of selecting the best layout of such farm in a given land area such that the total electrical power generated is maximized. The kites, typically, fly at high altitudes, sweep a greater area than that of traditional wind turbines, and move within a conic shaped volume with vertex on the ground station. Therefore, constraints concerning kite collision avoidance and terrain boundaries must be considered. The efficient use of a given land area by a set of KPS depends on the location of each unit, on its tether length and on the elevation angle. In this work, we formulate the KPS farm layout optimization problem. Considering a specific KPS and wind characteristics of the given location, we study the power curve as a function of the tether length and elevation angle. Combining these results with an area with specified length and width, we develop and implement a heuristic optimization procedure to devise the layout of a KPS farm that maximizes wind power generation. © 2019

2019

Joint scheduling of production and transport with alternative job routing in flexible manufacturing systems

Autores
Homayouni, SM; Fontes, DBMM;

Publicação

Abstract

2019

Modeling Supply Chain Network: A Need to Incorporate Financial Considerations

Autores
Borges, A; Fontes, DBMM; Gonçalves, JF;

Publicação
Springer Proceedings in Mathematics and Statistics

Abstract
In the past few years, important supply chain decisions have captured managerial interest. One of these decisions is the design of the supply chain network incorporating financial considerations, based on the idea that establishment and operating costs have a direct effect on the company’s financial performance. However, works on supply chain network design (SCND) incorporating financial decisions are scarce. In this work, we address a SCND problem in which operational and investment decisions are made in order to maximize the company value, measured by the Economic Value Added, while respecting the usual operational constraints, as well as financial ratios and constraints. This work extends current research by considering debt repayments and new capital entries as decision variables, improving on the calculation of some financial values, as well as introducing infrastructure dynamics; which together lead to greater value creation. © 2019, Springer Nature Switzerland AG.

2019

Selection of a Strategic Plan Using an Integrated AHP-Goal Programming Approach

Autores
Fontes, DBMM; Pereira, T; Oliveira, M;

Publicação
Bioinformatics and Biomedical Engineering - Lecture Notes in Computer Science

Abstract

Teses
supervisionadas

2017

A genetic algorithm to solve a multi-product distribution problem

Autor
Bruno Miguel Ribeiro Cretu

Instituição
UP-FEP

2017

Market Graph Analysis to the Portuguese Stock Market

Autor
Luís Pedro Airosa Carvalho Brás

Instituição
UP-FEP

2016

Application of a Genetic Algorithm to the design of a supply chain management with financial considerations

Autor
Maria Alexandra Teixeira Borges

Instituição
UP-FEP

2016

On Business Analytics: Dynamic Network Analysis for Descriptive Analytics and Multicriteria Decision Analysis for Prescriptive Analytics.

Autor
Márcia Daniela Barbosa Oliveira

Instituição
UP-FEP

2015

Um Algoritmo Genético Para O Planeamento De Rotas Com Considerações Ambientais

Autor
Andreia Patrícia Ferreira Sousa

Instituição
UP-FEP