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Sobre

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

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

2019

A BRKGA for the integrated scheduling problem in FMSs

Autores
Mahdi Homayouni, S; Fontes, DBMM; Fontes, FACC;

Publicação
Proceedings of the Genetic and Evolutionary Computation Conference Companion on - GECCO '19

Abstract

2019

A decision support system for TV self-promotion Scheduling

Autores
Fontes, DB; LIAAD-INESC L.A., Faculdade de Economia, Universidade do Porto, 4200-464 Porto, Portugal,; Pereira, PA; Fontes, FA; Universidade do Minho 4800-058 Guimarães, Portugal,; Universidade do Porto, 4200-465 Porto, Portugal,;

Publicação
International Journal of Advanced Trends in Computer Science and Engineering

Abstract
This paper describes a Decision Support System (DSS) that aims to plan and maintain the weekly self-promotion space for an over the air TV station. The self-promotion plan requires the assignment of several self-promotion advertisements to a given set of available time slots over a pre-specified planning period. The DSS consists of a data base, a statistic module, an optimization module, and a user interface. The input data is provided by the TV station and by an external audiometry company, which collects daily audience information. The statistical module provides estimates based on the data received from the audiometry company. The optimization module uses a genetic algorithm that can find good solutions quickly. The interface reports the solution and corresponding metrics and can also be used by the decision makers to manually change solutions and input data. Here, we report mainly on the optimization module, which uses a genetic algorithm (GA) to obtain solutions of good quality for realistic sized problem instances in a reasonable amount of time. The GA solution quality is assessed using the optimal solutions obtained by using a branch-and-bound based algorithm to solve instances of small size, for which optimality gaps below 1% are obtained.

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

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

Autor
Márcia Daniela Barbosa Oliveira

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

2015

Cloud Computing Adoption by Medium Sized enterprise A Case study of a Georgian Logistics and Distribution Company

Autor
Besarion Kacharava

Instituição
UP-FEP