Cookies
O website necessita de alguns cookies e outros recursos semelhantes para funcionar. Caso o permita, o INESC TEC irá utilizar cookies para recolher dados sobre as suas visitas, contribuindo, assim, para estatísticas agregadas que permitem melhorar o nosso serviço. Ver mais
Aceitar Rejeitar
  • Menu
Sobre

Sobre

Professor Catedrático na FEUP, no Departamento de Engenharia e Gestão Industrial, e na Porto Business School. Co-fundador da empresa LTPlabs (spin-off do INESC-TEC e da FEUP). Membro do Conselho de Curadores da Fundação Belmiro de Azevedo.

A sua área de atividade é Business Analytics e Management Science. Investiga, desenvolve e implementa modelos e métodos analíticos para auxiliar a tomada de decisão, resolvendo problemas de gestão em vários domínios (retalho, saúde, indústria e transportes), com um enfoque especial em Gestão de Operações.

Advanced Management Programme, INSEAD. Doutorado e agregado em Engenharia e Gestão Industrial (Universidade do Porto, 2007 e 2016). Licenciado em Gestão e Engenharia Industrial pela Faculdade de Engenharia da Universidade do Porto (FEUP, 2002) e  Foi investigador no Operations Research Center e na Sloan School of Management do Massachusetts Institute of Technology. Certified Analytics Professional pelo The Institute for Operations Research and the Management Sciences.

Anteriormente membro do Conselho de Administração do INESC-TEC Tecnologia e Ciência.Anteriormente, e Vice-diretor académico do Centro de Estudos Avançados Portugal da IBM.  Co-fundador da empresa Adjust Consulting (adquirida pela Glintt HealthCare).

Detalhes

Detalhes

019
Publicações

2023

Hybrid MCDM and simulation-optimization for strategic supplier selection

Autores
Saputro, TE; Figueira, G; Almada-Lobo, B;

Publicação
EXPERT SYSTEMS WITH APPLICATIONS

Abstract
Supplier selection for strategic items requires a comprehensive framework dealing with qualitative and quantitative aspects of a company's competitive priorities and supply risk, decision scope, and uncertainty. In order to address these aspects, this study aims to tackle supplier selection for strategic items with a multi-sourcing, taking into account multi-criteria, incorporating uncertainty of decision-makers judgment and supplier-buyer parameters, and integrating with inventory management which the past studies have not addressed well. We develop a novel two-phase solution approach based on integrated multi-criteria decision -making (MCDM) and multi-objective simulation-optimization (S-O). First, MCDM methods, including fuzzy AHP and interval TOPSIS, are applied to calculate suppliers' scores, incorporating uncertain decision makers' judgment. S-O then combines the (quantitative) cost-related criteria and considers supply disruptions and uncertain supplier-buyer parameters. By running this approach on data generated based on previous studies, we evaluate the impact of the decision maker's and the objective's weight, which are considered important in supplier selection.

2023

A Memetic Algorithm for the multi-product Production Routing Problem

Autores
Rodrigues, LF; Dos Santos, MO; Almada-Lobo, B;

Publicação
COMPUTERS & INDUSTRIAL ENGINEERING

Abstract
This article addresses the Production Routing Problem (PRP), which consists of determining, in an integrated way, production and inventory planning, and vehicle routing to minimize the costs involved. In the problem, a plant is responsible for producing several types of products to meet the known demand of a set of customers using a homogeneous fleet of vehicles over the planning horizon. In the literature, evolutionary approaches have not been explored in depth for the PRP, specifically for the problem with multiple products. Thus, this work mitigates this gap, presenting a novel Memetic Algorithm and testing its effectiveness on randomly generated sets of instances, comparing the results obtained with a commercial optimization solver. In our solution approach, several classic operators from the literature were implemented. Furthermore, we propose four novel genetic operators. In addition, we evaluated the proposed method's performance in classical instances of literature considering a single item. The computational experiments were carried out to assess the impact of the numerous parameter combinations involving the metaheuristic, and, from statistical analyses, we evidence the proposed technique's robustness. Computational experiments showed that our proposed method outperforms the commercial solver Gurobi in determining feasibly high-quality solutions, mainly on large instances for the PRP with multiple items.

2022

A comprehensive framework and literature review of supplier selection under different purchasing strategies

Autores
Saputro, TE; Figueira, G; Almada Lobo, B;

Publicação
COMPUTERS & INDUSTRIAL ENGINEERING

Abstract
Supplier selection has received substantial consideration in the literature since it is considered one of the key levers contributing to a firm's success. Selecting the right suppliers for different product items requires an appropriate problem framing and a suitable approach. Despite the vast literature on this topic, there is not a comprehensive framework underlying the supplier selection process that addresses those concerns. This paper formalizes a framework that provides guidance on how supplier selection should be formulated and approached for different types of items segmented in Kraljic's portfolio matrix and production policies. The framework derives from a thorough literature review, which explores the main dimensions in supplier selection, including sourcing strategy, decision scope and environment, selection criteria, and solution approaches. 326 papers, published from 2000 to 2021, were reviewed for said purpose. The results indicate that supplier selection regarding items with a high purchasing importance should lead to holistic selection criteria. In addition, items comprising a high complexity of supply and production activities should require integrated selection and different sources of uncertainty associated with decision scope and environment, respectively, to solve it, as well as hybrid approaches. There are still many research opportunities in the supplier selection area, particularly in the integrated selection problems and hybrid solution methods, as well as in the risk mitigation, sustainability goals, and new technology adoption.

2022

The multi-product inventory-routing problem with pickups and deliveries: Mitigating fluctuating demand via rolling horizon heuristics br

Autores
Neves Moreira, F; Almada Lobo, B; Guimaraes, L; Amorim, P;

Publicação
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW

Abstract
In this paper, we explore the value of considering simultaneous pickups and deliveries inmulti-product inventory-routing problems both with deterministic and uncertain demand. Wepropose a multi-commodity, develop an exact branch-and-cut algorithm with patching heuristicsto efficiently tackle this problem, and provide insightful analyses based on optimal plans. Thesimplicity of the proposed approach is an important aspect, as it facilitates its usage in practice,opposed to complicated stochastic or probabilistic methods. The computational experimentssuggest that in the deterministic demand setting, pickups are mainly used to balance initialinventories, achieving an average total cost reduction of 1.1%, while transshipping 2.4% oftotal demand. Under uncertain demand, pickups are used extensively, achieving cost savings of up to 6.5% in specific settings. Overall, our sensitivity analysis shows that high inventory costsand high degrees of demand uncertainty drive the usage of pickups, which, counter-intuitively, are not desirable in every case

2022

On the impact of adjusting the minimum life on receipt (MLOR) criterion in food supply chains

Autores
Santos, MJ; Martins, S; Amorim, P; Almada Lobo, B;

Publicação
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE

Abstract
The Minimum Life on Receipt (MLOR) is a widely used rule that imposes the minimum remaining age a food product must be delivered by the producer to the retailer. In practice, this rule is set by retailers and it is fixed, around 2/3 of the age of products regardless their shelf life. In this work, we study single and two echelon make-to-stock production-inventory problems for fixed-lifetime perishables. Mixed-integer linear optimization models are developed considering the MLOR rule both as decision variable and fixed parameter. When the MLOR rule is a variable, it is considered either a sole decision of the producer or a collaborative decision between retailer and producer. The goal of this work is to compare the supply chain performance considering this innovative setting of optimal MLOR (as a variable) against the traditional setting of fixed MLOR rule. The computational results suggest that allowing flexible MLOR rules according to the shelf life of products and the operational requirements of the producer benefit both entities in the supply chain. In particular, reducing the MLOR requirement in up to 12% does not interfere substantially with the average freshness of products arriving to the retailer, but reduces extensively surplus/waste generation at the producer while keeping a small amount of waste at the retailer.

Teses
supervisionadas

2022

Demand Forecasting in a Process Industry Context

Autor
João Dias Sampaio

Instituição
UP-FEUP

2022

Inventory Management in a Process Industry

Autor
Mariana Gonçalves Barrias

Instituição
UP-FEUP

2022

Previsão de Vendas no Setor de Bens de Consumo

Autor
Raquel Manuela Alves Machado

Instituição
UP-FEUP

2022

Fulfillment in online retail: making real-time decisions with explainable artificial intelligence

Autor
Sérgio Vasconcelos Castro

Instituição
UP-FEUP

2022

Towards Sustainable Product and Supply Chain Development in the Aerospace Industry

Autor
Nuno Bernardo Gonçalves Falcão e Cunha

Instituição
UP-FEUP