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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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007
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.

2020

Retail shelf space planning problems: A comprehensive review and classification framework

Authors
Bianchi Aguiar, T; Hübner, A; Carravilla, MA; Oliveira, JF;

Publication
European Journal of Operational Research

Abstract
The retail shelf space planning problem has long been addressed by Marketing and Operations Research (OR) professionals and researchers, with the first empirical studies tracing back to the 1960s and the first modelling approaches back to the 1970s. Due to this long history, this field presents a wide range of different mathematical modelling approaches that deal with the decisions surrounding a set of products and not only define their space assignment and related quantity, but also their vertical and horizontal positioning within a retail shelf. These decisions affect customer demand, namely in the form of space- and position-dependent demand and replenishment requirements. Current literature provides either more comprehensive decision models with a wide range of demand effects but limited practical applicability, or more simplistic model formulations with greater practical application but limited consideration of the associated demand. Despite the recent progress seen in this research area, no work has yet systematised published research with a clear focus on shelf space planning. As a result, there is neither any up-to-date structured literature nor a unique model approach, and no benchmark sets are available. This paper provides a description and a state-of-the-art literature review of this problem, focusing on optimisation models. Based on this review, a classification framework is proposed to systematise the research into a set of sub-problems, followed by a unified approach with a univocal notation of model classes. Future lines of research point to the most promising open questions in this field. © 2020 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.

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

O Impacto da Produtividade na Gestão Industrial – Uma análise aplicada ao sector do móvel e do mobiliário de madeira e derivados em Portugal

Author
Jonas André Rodrigues Henriques de Lima

Institution
UP-FEUP