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About

My main area of scientific activity is Operations Research and Management Science. Within Operations Research my main application area are the Cutting and Packing Problems, while from the techniques viewpoint my research is centered in the use and development of Metaheuristics approaches.

Cutting and Packing problems are hard combinatorial optimization problems that arise under several practical contexts, whenever big pieces of raw-material have to be cut into smaller items, or small items have to be packed inside a larger container, so that waste is minimized. These problems include hard geometric constraints when dealing with the optimization layer. I have also worked on Vehicle Routing Problem. My research on Lotsizing and Scheduling problems in industrial contexts mainly builds on my expertise on Metaheuristics.

More recently I have worked on the use of the quantitative methods, provided by Operations Research and Management Science, to support decision making in Higher Education institutions management, which includes workload models, sustainability, institutional benchmarking and assessment and evaluation of institutions and teaching staff.

Interest
Topics
Details

Details

009
Publications

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

Models for the two-dimensional level strip packing problem - a review and a computational evaluation

Authors
Bezerra, VMR; Leao, AAS; Oliveira, JF; Santos, MO;

Publication
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY

Abstract
The two-dimensional level strip packing problem has received little attention from the scientific community. To the best of our knowledge, the most competitive model is the one proposed in 2004 by Lodi et al., where the items are packed by levels. In 2015, an arc flow model addressing the two-dimensional level strip cutting problem was proposed by Mrad. The literature presents some mathematical models, despite not addressing specifically the two-dimensional level strip packing problem, they are efficient and can be adapted to the problem. In this paper, we adapt two mixed integer linear programming models from the literature, rewrite the Mrad's model for the strip packing problem and add well-known valid inequalities to the model proposed by Lodi et al. Computational results were performed on instances from the literature and show that the model put forward by Lodi et al. with valid inequalities outperforms the remaining models with respect to the number of optimal solutions found.

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

Data mining based framework to assess solution quality for the rectangular 2D strip-packing problem

Authors
Neuenfeldt Junior, A; Silva, E; Gomes, M; Soares, C; Oliveira, JF;

Publication
Expert Systems with Applications

Abstract
In this paper, we explore the use of reference values (predictors) for the optimal objective function value of hard combinatorial optimization problems, instead of bounds, obtained by data mining techniques, and that may be used to assess the quality of heuristic solutions for the problem. With this purpose, we resort to the rectangular two-dimensional strip-packing problem (2D-SPP), which can be found in many industrial contexts. Mostly this problem is solved by heuristic methods, which provide good solutions. However, heuristic approaches do not guarantee optimality, and lower bounds are generally used to give information on the solution quality, in particular, the area lower bound. But this bound has a severe accuracy problem. Therefore, we propose a data mining-based framework capable of assessing the quality of heuristic solutions for the 2D-SPP. A regression model was fitted by comparing the strip height solutions obtained with the bottom-left-fill heuristic and 19 predictors provided by problem characteristics. Random forest was selected as the data mining technique with the best level of generalisation for the problem, and 30,000 problem instances were generated to represent different 2D-SPP variations found in real-world applications. Height predictions for new problem instances can be found in the regression model fitted. In the computational experimentation, we demonstrate that the data mining-based framework proposed is consistent, opening the doors for its application to finding predictions for other combinatorial optimisation problems, in particular, other cutting and packing problems. However, how to use a reference value instead of a bound, has still a large room for discussion and innovative ideas. Some directions for the use of reference values as a stopping criterion in search algorithms are also provided. © 2018 Elsevier Ltd

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

Otimização do parqueamento de aeronaves em hangares de manutenção

Author
Bruno Manuel João Estevinho

Institution
UP-FEUP

2019

The Social Impact of the use of Cyber-Physical Systems in Manufacturing

Author
Diogo Manuel Rebelo de Azevedo Seabra Pimenta

Institution
UP-FEUP

2019

A Simulation-Optimization Model to Determine Fashion Delivery Patterns

Author
Daniela Timóteo Martins de Pinho

Institution
UP-FEUP

2019

An Optimization Approach to Production Planning with Scheduling Dependent Capacity and Resource Allocation

Author
Rafael Leonardo Ribeiro de Carvalho

Institution
UP-FEUP

2018

Heurísticas para problemas de corte de formas irregulares

Author
Duarte Nuno de Azevedo Fonseca

Institution
UP-FEUP