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Maria Antónia Carravilla @ FEUP

Maria Antónia Carravilla is a teacher at Faculdade de Engenharia da Universidade do Porto (FEUP) since 1985, visiting professor at Universidade de São Paulo (USP), teacher at Porto Business School in the Executive and Magellan MBA's, and a researcher at INESC-TEC since 1990.

Maria Antónia is the Director of the Doctoral Program in Engineering and Industrial Management (PRODEGI @ FEUP) since 2016.

Maria Antónia Carravilla has been responsible for several R&D contracts with industry, services and public administration. These contracts resulted in reports and decision support systems that proved to be very useful tools for these organizations, leading to long-lasting collaborations with FEUP. The pure research contracts were mainly founded by FCT and are mainly related with the application of constraint programming to the resolution of nesting problems. The R&D contracts and the research contracts were the basis for the theses of several PhD students.

Maria Antónia Carravilla has been a member of the Executive Committee of FEUP for 9 years as Pro-Dean for management and control. She was the Director of the Financial Services and head of the Management Office of FEUP for 7 years. She has been responsible for the Jupiter Project that managed the move of FEUP to the new premises in 2000. She has also been responsible for the projects that resulted in the implementation in FEUP of workflows related with the Financial Services. Within the management office of FEUP she led studies related with indicators for higher education institutions and supervised a masters thesis on sustainability indicators for higher education institutions.

As a teacher at FEUP, Maria Antónia Carravilla has been responsible for several courses related with Operations Research, Operations Management and Logistics that were taught at the BSc, MSc and PhD levels. She has supervised MSc students whose theses were developed in academia as well as in industry.

Maria Antónia Carravilla received in 2009, the first time it has been awarded, FEUP’s Award for Pedagogical Excellence that aims to award the best teacher of FEUP for the past 5 years.

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006
Publications

2020

Tactical sales and operations planning: A holistic framework and a literature review of decision-making models

Authors
Pereira, DF; Oliveira, JF; Carravilla, MA;

Publication
International Journal of Production Economics

Abstract
Tactical Sales and Operations Planning (S&OP) has emerged as an extension of the aggregate production planning, integrating mid-term decisions from procurement, production, distribution, and sales in a single plan. Despite the growing interest in the subject, past synthesizing research has focused more on the qualitative and procedural aspects of the topic rather than on modeling approaches to the problem. This paper conducts a review of the existing decision-making, i.e., optimization, models supporting S&OP. A holistic framework comprising the decisions involved in this planning activity is presented. The reviewed literature is arranged within the framework and grouped around different streams of literature which have been extending the aggregate production planning. Afterwards, the papers are classified according to the modeling approaches employed by past researchers. Finally, based on the characterization of the level of integration of different business functions provided by existing models, the review demonstrates that there are no synthesizing models characterizing the overall S&OP problem and that, even in the more comprehensive approaches, there is potential to include additional decisions that would be the basis for more sophisticated and proactive S&OP programs. We do expect this paper contributes to set the ground for more oriented and structured research in the field. © 2020 Elsevier B.V.

2020

Irregular packing problems: A review of mathematical models

Authors
Leao, AAS; Toledo, FMB; Oliveira, JF; Carravilla, MA; Alvarez Valdes, R;

Publication
European Journal of Operational Research

Abstract
Irregular packing problems (also known as nesting problems)belong to the more general class of cutting and packing problems and consist of allocating a set of irregular and regular pieces to larger rectangular or irregular containers, while minimizing the waste of material or space. These problems combine the combinatorial hardness of cutting and packing problems with the computational difficulty of enforcing the geometric non-overlap and containment constraints. Unsurprisingly, nesting problems have been addressed, both in the scientific literature and in real-world applications, by means of heuristic and metaheuristic techniques. However, more recently a variety of mathematical models has been proposed for nesting problems. These models can be used either to provide optimal solutions for nesting problems or as the basis of heuristic approaches based on them (e.g. matheuristics). In both cases, better solutions are sought, with the natural economic and environmental positive impact. Different modeling options are proposed in the literature. We review these mathematical models under a common notation framework, allowing differences and similarities among them to be highlighted. Some insights on weaknesses and strengths are also provided. By building this structured review of mathematical models for nesting problems, research opportunities in the field are proposed. © 2019 Elsevier B.V.

2019

A co-evolutionary matheuristic for the car rental capacity-pricing stochastic problem

Authors
Oliveira, BB; Carravilla, MA; Oliveira, JF; Costa, AM;

Publication
European Journal of Operational Research

Abstract

2019

A Benders Decomposition Algorithm for the Berth Allocation Problem

Authors
Barbosa, F; Oliveira, JF; Carravilla, MA; Curcio, EF;

Publication
Springer Proceedings in Mathematics and Statistics

Abstract
In this paper we present a Benders decomposition approach for the Berth Allocation Problem (BAP). Benders decomposition is a cutting plane method that has been widely used for solving large-scale mixed integer linear optimization problems. On the other hand, the Berth Allocation Problem is a NP-hard and large-scale problem that has been gaining relevance both from the practical and scientific points of view. In this work we address the discrete and dynamic version of the problem, and develop a new decomposition approach and apply it to a reformulation of the BAP based on the Heterogeneous Vehicle Routing Problem with Time Windows (HVRPTW) model. In a discrete and dynamic BAP each berth can moor one vessel at a time, and the vessels are not all available to moor at the beginning of the planning horizon (there is an availability time window). Computational tests are run to compare the proposed Benders Decomposition with a state-of-the-art commercial solver. © 2019, Springer Nature Switzerland AG.

2019

Optimality in nesting problems: New constraint programming models and a new global constraint for non-overlap

Authors
Cherri, LH; Carravilla, MA; Ribeiro, C; Bragion Toledo, FMB;

Publication
Operations Research Perspectives

Abstract
In two-dimensional nesting problems (irregular packing problems) small pieces with irregular shapes must be packed in large objects. A small number of exact methods have been proposed to solve nesting problems, typically focusing on a single problem variant, the strip packing problem. There are however several other variants of the nesting problem which were identified in the literature and are very relevant in the industry. In this paper, constraint programming (CP) is used to model and solve all the variants of irregular cutting and packing problems proposed in the literature. Three approaches, which differ in the representation of the variable domains, in the way they deal with the core constraints and in the objective functions, are the basis for the three models proposed for each variant of the problem. The non-overlap among pieces, which must be enforced for all the problem variants, is guaranteed through the new global constraint NoOverlap in one of the proposed approaches. Taking the benchmark instances for the strip-packing problem, new instances were generated for each problem variant. Extensive computational experiments were run with these problem instances from the literature to evaluate the performance of each approach applied to each problem variant. The models based on the global constraint NoOverlap performed consistently better for all variants due to the increased propagation and to the low memory usage. The performance of the CP model for the strip packing problem with the global constraint NoOverlap was then compared with the Dotted Board with Rotations using larger instances from the literature. The experiments show that the CP model with global constraint NoOverlap can quickly find good quality solutions in shorter computational times even for large instances. © 2019

Supervised
thesis

2019

Conceção e desenvolvimento de um sistema de apoio à decisão para gestão de inventários no retalho

Author
Edgar Filipe dos Anjos Couto

Institution
UP-FEUP

2019

Airport Slot Allocation Processes. A heuristic approach

Author
Rafael Filipe dos Santos

Institution
UP-FEUP

2018

Front Office de uma empresa de bebidas: Indicadores de Desempenho do Serviço ao Cliente

Author
Bárbara Dias Pereira

Institution
UP-FEUP

2018

Fleet and revenue management in car rental: quantitative approaches for optimization under uncertainty

Author
Maria Beatriz Brito Oliveira

Institution
UP-FEUP

2018

Airport Slot Allocation Processes. A heuristic approach

Author
Rafael Filipe dos Santos

Institution
UP-FEUP