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About

About

I am an Assistant Professor with habilitation at Faculdade de Economia da Universidade do Porto (FEP) and board member of LIAAD, Laboratório de Inteligência Artificial e de Apoio à Decisão of UP. LIAAD is a unit of INESC TEC since 2007. I am Ph.D. in Management Science, Imperial College of London – Business School, MSc. In Operational Research, The London School of Economics and Political Sciences, and I have a first degree (5-years) in Electrical Engineering and Computer, Faculdade de Engenharia da Universidade do Porto. Visiting Professor at University of Florida - Department of Industrial and Systems Engineering (2007/08) and at Texas A&M University – Department Industrial & Systems Engineering (2015-16).

My research interests include developing and applying Operational Research and Artificial Intelligence techniques for decision support in Management problems (including production, storage, logistics and transportation, and services), with particular interest on combinatorial optimization applications.

At FEP I have been lecturing, mainly in English, Operational Research and Operations Management to undergraduates, Logistics, Decision Analysis, and Optimization to Master students and Ph.D. candidates. At FEP have also been involved in several boards and councils (Representative Council, Scientific Board, Scientific Committee of the Ph.D. in Management, among others).

Interest
Topics
Details

Details

  • Name

    Dalila Fontes
  • Cluster

    Computer Science
  • Role

    Senior Researcher
  • Since

    01st January 2011
003
Publications

2019

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

Authors
Homayouni, SM; Fontes, DBMM;

Publication

Abstract

2019

Modeling Supply Chain Network: A Need to Incorporate Financial Considerations

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

Publication
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

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

Publication
Bioinformatics and Biomedical Engineering - Lecture Notes in Computer Science

Abstract

2019

A BRKGA for the integrated scheduling problem in FMSs

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

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

Abstract

2019

A decision support system for TV self-promotion Scheduling

Authors
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,;

Publication
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.

Supervised
thesis

2017

A genetic algorithm to solve a multi-product distribution problem

Author
Bruno Miguel Ribeiro Cretu

Institution
UP-FEP

2017

Market Graph Analysis to the Portuguese Stock Market

Author
Luís Pedro Airosa Carvalho Brás

Institution
UP-FEP

2016

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

Author
Maria Alexandra Teixeira Borges

Institution
UP-FEP

2016

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

Author
Márcia Daniela Barbosa Oliveira

Institution
UP-FEP

2015

In-store Order Picking Routing: A Biased Random-Key Genetic Algorithm Approach

Author
Tiago Miguel Ferreira Das Neves Salgado

Institution
UP-FEP