Cookies
Usamos cookies para melhorar nosso site e a sua experiência. Ao continuar a navegar no site, você aceita a nossa política de cookies. Ver mais
Fechar
  • Menu
Sobre
Download foto HD

Sobre

A minha área de investigação principal é a Investigação Operacional e os Métodos Quantitativos aplicados à Gestão. Neste âmbito, a área de aplicação principal são os problema de Cortes e Empacotamentos enquanto, do ponto de vista das técnicas, a minha investigação está centrada na utilização e desenvolvimento de abordagens baseadas em metaheurísticas.

Os problemas de Cortes e Empacotamentos são, na sua maioria, problemas de optimização combinatória NP-difíceis e ocorrem em vários contextos práticos sempre que peças grandes de matéria-prima tenham que ser cortadas em peças mais pequenas ou, alternativamente, itens pequenos tenham que ser empacotados dentro de um contentor maior, de forma a que o desperdício, de matéria-prima ou espaço, seja minimizado. Estes problemas incluem difíceis restrições geométricas na sua camada de optimização. Também trabalhei em problemas de determinação de rotas de veículos. A minha investigação em problemas de sequenciamento de determinação de lotes em contextos industriais deriva fundamentalmente do meu trabalho com metaheurísticas.

Mais recentemente tenho trabalhado na utilização dos métodos quantitativos providenciados pela Investigação Operacional no apoio à decisão na gestão de instituições do ensino superior, o que inclui a avaliação institucional e de recursos humanos, "benchmarking", sustentabilidade e modelos de avaliação de carga e desempenho.

Tópicos
de interesse
Detalhes

Detalhes

009
Publicações

2020

Irregular packing problems: A review of mathematical models

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

Publicação
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

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

Publicação
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

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

Publicação
European Journal of Operational Research

Abstract

2019

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

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

Publicação
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

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

Publicação
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.

Teses
supervisionadas

2019

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

Autor
Rafael Leonardo Ribeiro de Carvalho

Instituição
UP-FEUP

2019

Otimização do parqueamento de aeronaves em hangares de manutenção

Autor
Bruno Manuel João Estevinho

Instituição
UP-FEUP

2019

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

Autor
Diogo Manuel Rebelo de Azevedo Seabra Pimenta

Instituição
UP-FEUP

2019

A Simulation-Optimization Model to Determine Fashion Delivery Patterns

Autor
Daniela Timóteo Martins de Pinho

Instituição
UP-FEUP

2018

Heurísticas para problemas de corte de formas irregulares

Autor
Duarte Nuno de Azevedo Fonseca

Instituição
UP-FEUP