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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

2018

Evaluating suppliers in the olive oil sector using AHP

Authors
Fontes, DBMM; Pereira, T; Dias, E;

Publication
Springer Proceedings in Mathematics and Statistics

Abstract
This work proposes a multi-criteria decision making approach to help assessing and selecting suppliers in the olive oil sector. Olive oil is a protected agricultural product, by region and origin certificate. Therefore to select a supplier, it is of utter importance to inspect and test (taste, colour, smell, density, among others) the olive oil in addition to the supplying company. The identification of possible suppliers was done in two stages: firstly, the region of origin from which to choose possible suppliers was identified and then potential suppliers were evaluated on a set of characteristics for which minimum threshold values were set. From this study, which is not part of the research reported here, we were able to identify the suppliers of interest. Due to the several characteristics and characteristic dimensions used to choose a supplier we resort to the Analytic Hierarchy Process to rank them, this way allowing for a better choice. The rank obtained is robust as the top ranked supplier remains the same for any reasonable change in the criteria weighs and in the evaluation of the suppliers on each criterion. The involved company found the results of value, as well as the lessons learned by addressing the supplier evaluation problem using a more systematic approach. © Springer International Publishing AG 2018.

2018

Evaluating vehicle painting plans in an automobile assembly plant using an integrated AHP-PROMETHEE approach

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

Publication
International Transactions in Operational Research

Abstract
The painting activity is one of the most complex and important activities in automobile manufacturing. The inherent complexity of the painting activity and the frequent need for repainting usually turn the painting process into a bottleneck in automobile assembly plants, which is reflected in higher operating costs and longer overall cycle times. One possible approach for optimizing the performance of the paint shop is to improve the efficiency of the color planning. This can be accomplished by evaluating the relative merits of a set of vehicle painting plans. Since this problem has a multicriteria nature, we resort to the multicriteria decision analysis (MCDA) methodology to tackle it. A recent trend in the MCDA field is the development of hybrid approaches that are used to achieve operational synergies between different methods. Here we apply, for the first time, an integrated approach that combines the strengths of the analytic hierarchy process (AHP) and the Preference Ranking Organization METHod for Enrichment Evaluations (PROMETHEE), aided by Geometrical Analysis for Interactive Aid (GAIA), to the problem of assessing alternative vehicle painting plans. The management of the assembly plant found the results of value and is currently using them in order to schedule the painting activities such that an enhancement of the operational efficiency of the paint shop is obtained. This efficiency gain has allowed the management to bid for a new automobile model to be assembled at this specific plant. © 2015 International Federation of Operational Research Societies.

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 de Oliveira

Institution
UP-FEP

2015

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

Author
Besarion Kacharava

Institution
UP-FEP