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About

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.

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Details

Details

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Publications

2022

A Diversity-Based Genetic Algorithm for Scenario Generation

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

Publication
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH

Abstract

2022

Merging make-to-stock/make-to-order decisions into sales and operations planning: A multi-objective approach

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

Publication
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE

Abstract
With the advent of mass customization and product proliferation, the appearance of hybrid Make-toStock(MTS)/Make-to-Order(MTO) policies arise as a strategy to cope with high product variety maintaining satisfactory lead times. In companies operating under this reality, Sales and Operations Planning (S&OP) practices must be adapted accordingly during the coordinated planning of procurement, production, logistics, and sales activities. This paper proposes a novel S&OP decision-making framework for a flow shop/batch company that produces standard products under an MTS strategy and customized products under an MTO strategy. First, a multi-objective mixed-integer programming model is formulated to characterize the problem. Then, a matrix containing the different strategies a firm in this context may adopt is proposed. This rationale provides a business-oriented approach towards the analysis of different plans and helps to frame the different Pareto-optimal solutions given the priority on MTS or MTO segments and the management positioning regarding cost minimization or service level orientation. The research is based on a real case faced by an electric cable manufacturer. The computational experiments demonstrate the applicability of the proposed methodology. Our approach brings a practical, supply chain-oriented, and mid-term perspective on the study of operations planning policies in MTS/MTO contexts.

2022

A C++ application programming interface for co-evolutionary biased random-key genetic algorithms for solution and scenario generation

Authors
Oliveira, BB; Carravilla, MA; Oliveira, JF; Resende, MGC;

Publication
OPTIMIZATION METHODS & SOFTWARE

Abstract
This paper presents a C++ application programming interface for a co-evolutionary algorithm for solution and scenario generation in stochastic problems. Based on a two-space biased random-key genetic algorithm, it involves two types of populations that are mutually impacted by the fitness calculations. In the solution population, high-quality solutions evolve, representing first-stage decisions evaluated by their performance in the face of the scenario population. The scenario population ultimately generates a diverse set of scenarios regarding their impact on the solutions. This application allows the straightforward implementation of this algorithm, where the user needs only to define the problem-dependent decoding procedure and may adjust the risk profile of the decision-maker. This paper presents the co-evolutionary algorithm and structures the interface. We also present some experiments that validate the impact of relevant features of the application. © 2021 Informa UK Limited, trading as Taylor & Francis Group.

2022

On-line three-dimensional packing problems: A review of off-line and on-line solution approaches

Authors
Ali, S; Ramos, AG; Carravilla, MA; Oliveira, JF;

Publication
COMPUTERS & INDUSTRIAL ENGINEERING

Abstract

2022

First-mile logistics parcel pickup: Vehicle routing with packing constraints under disruption

Authors
Giménez Palacios, I; Parreño, F; Álvarez Valdés, R; Paquay, C; Oliveira, BB; Carravilla, MA; Oliveira, JF;

Publication
Transportation Research Part E: Logistics and Transportation Review

Abstract

Supervised
thesis

2021

Detection of Pulmonary Lesions for COVID-19 Screening

Author
Joana Soares Maximino

Institution
UP-FCUP

2021

Integrating Production Planning in a Manufacturing Execution System (MES)

Author
João Pedro da Costa Silva Pereira

Institution
UP-FEUP

2021

Airport Slot Allocation - instances and resolution methods

Author
Sofia Sousa Lobo

Institution
UP-FEUP

2021

Developing a learning solution approach for the on-line three-dimensional bin packing problems

Author
Sara Ali

Institution
UP-FEUP

2021

LIGTHWEIGHT + POST-QUANTUM CRYPTOGRAPHIES

Author
Henrique José Carvalho Faria

Institution
UM