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Sobre

Sobre

Elsa Silva é investigadora no Centro de Engenharia e Gestão Industrial do INESC TEC e Professora Auxiliar convidada do Departamento de Produção e Sistemas da Universidade do Minho.

É doutorada em Engenharia Industrial e de Sistemas desde 2012 pela Universidade do Minho. Os seus principais interesses de investigação incluem a capacidade de resolver problemas de optimização combinatória difíceis e de grande escala que surgem em várias áreas, tais como problemas de corte e empacotamento e operações de retalho, utilizando abordagens híbridas de programação linear e meta-heurísticas.

As principais contribuições da investigação da Elsa Silva têm sido em problemas de corte e empacotamento (C&P). Algoritmos pioneiros foram desenvolvidos combinando modelos matemáticos, métodos de decomposição e heurísticas para resolver aplicações práticas que até agora não foram estudadas realisticamente. Esta foi uma contribuição importante para o avanço do conhecimento na área dos C&P.

As aplicações práticas abordadas foram: Problema de Alocação de Espaço em Prateleira, Problema de Empacotamento de Tiras na indústria têxtil, Problema de Carregamento de Contentores com estabilidade, limite de peso, balanceamento de carga e restrições de entregas múltiplas. Outra contribuição importante na área de C&P foi o gerador de instâncias para todos os tipos de problemas de C&P retangulares 2D e 3D.

Tópicos
de interesse
Detalhes

Detalhes

  • Nome

    Elsa Marília Silva
  • Cargo

    Investigador Colaborador Externo
  • Desde

    01 fevereiro 2012
005
Publicações

2024

Pallets delivery: Two matheuristics for combined loading and routing

Autores
Silva, E; Ramos, AG; Moura, A;

Publicação
EXPERT SYSTEMS WITH APPLICATIONS

Abstract
The implementation of novel regulatory and technical requirements for the distribution of vehicle axle weights in road freight transport introduces a new set of constraints on vehicle routing. Until now, axle weight distribution in determining the load plan for freight transport units has been overlooked in the vehicle routing process. Compliance with these axle weight constraints has become paramount for road freight transport companies, since noncompliance with the axle weight distribution legislation translates into heavy fines. This work aims to provide a tool capable of generating cargo loading plans and routing sequences for a palletised cargo distribution problem. The problem addressed integrates the capacitated vehicle routing problem with time window and the two-dimensional loading problem with load balance constraints. Two integrative solution approaches are proposed, one giving greater importance to the routing and the other prioritising the loading. In addition, a novel MILP model is proposed for the 2D pallet loading problem with load-balance constraints that take advantage of the standard dimension of the pallets. Extensive computational experiments were performed with a set of well-known literature benchmark instances, extended to incorporate additional features. The computational results show the effectiveness of the proposed approaches.

2023

Mathematical models for the two-dimensional variable-sized cutting stock problem in the home textile industry

Autores
Salem, KH; Silva, E; Oliveira, JF; Carravilla, MA;

Publicação
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH

Abstract
In this paper, we consider the two-dimensional Variable-Sized Cutting Stock Problem (2D-VSCSP) with guillotine constraint, applied to the home textile industry. This is a challenging class of real-world prob-lems where, given a set of predefined widths of fabric rolls and a set of piece types, the goal is to de-cide the widths and lengths of the fabric rolls to be produced, and to generate the cutting patterns to cut all demanded pieces. Each piece type considered has a rectangular shape with a specific width and length and a fixed demand to be respected. The main objective function is to minimize the total amount of the textile materials produced/cut to satisfy the demand. According to Wascher, Hau ss ner, & Schu-mann (2007), the addressed problem is a Cutting Stock Problem (CSP), as the demand for each item is greater than one. However, in the real-world application at stake, the demand for each item type is not very high (below ten for all item types). Therefore, addressing the problem as a Bin-Packing Problem (BPP), in which all items are considered to be different and have a unitary demand, was a possibility. For this reason, two approaches to solve the problems were devised, implemented, and tested: (1) a CSP model, based on the well-known Lodi and Monaci (2003) model (3 variants), and (2) an original BPP-based model. Our research shows that, for this level of demand, the new BPP model is more competitive than CSP models. We analyzed these different models and described their characteristics, namely the size and the quality of the linear programming relaxation bound for solving the basic mono-objective variant of the problem. We also propose an epsilon-constraint approach to deal with a bi-objective extension of the problem, in which the number of cutting patterns used must also be minimized. The quality of the models was evaluated through computational experiments on randomly generated instances, yielding promising results.(c) 2022 Published by Elsevier B.V.

2023

The Floating-Cuts model: a general and flexible mixed-integer programming model for non-guillotine and guillotine rectangular cutting problems

Autores
Silva, E; Oliveira, JF; Silveira, T; Mundim, L; Carravilla, MA;

Publicação
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE

Abstract
Cutting and packing problems are challenging combinatorial optimization problems that have many rel-evant industrial applications and arise whenever a raw material has to be cut into smaller parts while minimizing waste, or products have to be packed, minimizing the empty space. Thus, the optimal solution to these problems has a positive economic and environmental impact. In many practical applications, both the raw material and the cut parts have a rectangular shape, and cut-ting plans are generated for one raw material rectangle (also known as plate) at a time. This is known in the literature as the (two-dimensional) rectangular cutting problem. Many variants of this problem may arise, led by cutting technology constraints, raw-material characteristics, and different planning goals, the most relevant of which are the guillotine cuts. The absence of the guillotine cuts imposition makes the problem harder to solve to optimality.Based on the Floating-Cuts paradigm, a general and flexible mixed-integer programming model for the general rectangular cutting problem is proposed. To the best of our knowledge, it is the first mixed inte-ger linear programming model in the literature for both non-guillotine and guillotine problems. The basic idea of this model is a tree search where branching occurs by successive first-order non-guillotine-type cuts. The exact position of the cuts is not fixed, but instead remains floating until a concrete small rect-angle (also known as item) is assigned to a child node. This model does not include decision variables either for the position coordinates of the items or for the coordinates of the cuts. Under this framework, it was possible to address various different variants of the problem.Extensive computational experiments were run to evaluate the model's performance considering 16 dif-ferent problem variants, and to compare it with the state-of-the-art formulations of each variant. The results confirm the power of this flexible model, as, for some variants, it outperforms the state-of-the-art approaches and, for the other variants, it presents results fairly close to the best approaches. But, even more importantly, this is a new way of looking at these problems which may trigger even better approaches, with the consequent economic and environmental benefits.

2023

Cutting and packing problems under uncertainty: literature review and classification framework

Autores
Salem, KH; Silva, E; Oliveira, JF;

Publicação
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH

Abstract
Cutting and packing problems are hard combinatorial optimization problems that arise in several manufacturing and process industries or in their supply chains. The solution of these problems is not only a scientific challenge but also has a large economic impact, as it contributes to the reduction of one of the major cost factors for many production sectors, namely raw materials, together with a positive environmental impact. The explicit consideration of uncertainty when solving cutting and packing problems with optimization techniques is crucial for a wider adoption of research results by companies. However, current research has paid little attention to the role of uncertainty in these problems. In this paper, we review the existing literature on uncertainty in cutting and packing problems, propose a classification framework, and highlight the many research gaps and opportunities for scientific contributions.

2023

An introduction to the two-dimensional rectangular cutting and packing problem

Autores
Oliveira, O; Gamboa, D; Silva, E;

Publicação
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH

Abstract
Cutting and packing problems have been widely studied in the last decades, mainly due to the variety of industrial applications where the problems emerge. This paper presents an overview of the solution approaches that have been proposed for solving two-dimensional rectangular cutting and packing problems. The main emphasis of this work is on two distinct problems that belong to the cutting and packing problem family. The first problem aims to place onto an object the maximum-profit subset of items, that is, output maximization, while the second one aims to place all the items using as few identical objects as possible, that is, input minimization. The objective of this paper is not to be exhaustive but to provide a solid grasp on two-dimensional rectangular cutting and packing problems by describing their most important solution approaches.

Teses
supervisionadas

2021

Melhoria Operacional e Redução dos Tempos de Setup em Processos de Transformação de Cartão Canelado

Autor
Sofia Choon Rei

Instituição
UP-FEUP

2021

Early detection and identification of plant diseases caused by bacteria based on proximal sensingfrom a precision agriculture perspective

Autor
Mafalda Alexandra Reis Pereira

Instituição
UP-FCUP

2020

O problema de roteamento de veículos com custos de combustível dependentes do peso

Autor
DIOGO JOSÉ LAGES PEREIRA MORGADO RIBEIRO

Instituição
IPP-ISEP

2019

Framework de gestão de notícias regionais em canais de televisão

Autor
Diogo Santos Tavares

Instituição
UP-FEUP

2019

Efficient Heuristics for Two-Dimensional Cutting and Packing Problems

Autor
Óscar António Maia de Oliveira

Instituição
UP-FEUP