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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

  • Nome

    Bernardo Almada-Lobo
  • Cargo

    Diretor
  • Desde

    01 dezembro 2010
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.

2023

Predicting the future: introducing business analytics to endoscopy units

Autores
Pinho, R; Veloso, R; Estevinho, MM; Rodrigues, T; Almada Lobo, B; Amorim Lopes, M; Freitas, T;

Publicação
REVISTA ESPANOLA DE ENFERMEDADES DIGESTIVAS

Abstract
Background and aims: currently, most endoscopy software only provides limited statistics of past procedures, while none allows patterns to be extrapolated. To overcome this need, the authors applied business analytic models to pre-dict future demand and the need for endoscopists in a ter-tiary hospital Endoscopy Unit. Methods: a query to the endoscopy database was per-formed to retrieve demand from 2015 to 2021. The graphi-cal inspection allowed inferring of trends and seasonality, perceiving the impact of the COVID-19 pandemic, and se-lecting the best forecasting models. Considering COVID-19's impact in the second quarter of 2020, data for esoph-agogastroduodenoscopy (EGD) and colonoscopy was estimated using linear regression of historical data. The actual demand in the first two quarters of 2022 was used to validate the models. Results: during the study period, 53,886 procedures were requested. The best forecasting models were: a) simple sea-sonal exponential smoothing for EGD, colonoscopy and percutaneous endoscopic gastrostomy (PEG); b) double ex-ponential smoothing for capsule endoscopy and deep en-teroscopy; and c) simple exponential smoothing for endo-scopic retrograde cholangiopancreatography (ERCP) and endoscopic ultrasound (EUS). The mean average percent-age error ranged from 6.1 % (EGD) to 33.5 % (deep en - teroscopy). Overall, 8,788 procedures were predicted for 2022. The actual demand in the first two quarters of 2022 was within the predicted range. Considering the usual time allocation for each technique, 3.2 full-time equivalent en-doscopists (40 hours-dedication to endoscopy) will be re-quired to perform all procedures in 2022. Conclusions: the incorporation of business analytics into the endoscopy software and clinical practice may enhance resource allocation, improving patient-focused deci-sion-making and healthcare quality.

2023

Robust supply chain design with suppliers as system integrators: an aerospace case study

Autores
Cunha, NFE; Gan, TS; Curcio, E; Amorim, P; Almada Lobo, B; Grunow, M;

Publicação
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH

Abstract
Original Equipment Manufacturers (OEMs) have sought new supply chain paradigms that allowed them to focus on core activities, i.e. overall product design and commercialisation. This pursuit led to partnerships with a new generation of tier-1 strategic suppliers acting as integrators. Integrators are not only responsible for system supply, but also for system design. However, critical integrators were not able to live up to their new roles, which led to costly delays in development and production. These failures highlight the ineptitude of current risk management practices employed by OEMs. To support OEMs in implementing a more differentiated and suitable approach to the use of integrators, this paper proposes a mathematical programming model for Supply Chain Design (SCD). Instead of looking at the introduction of integrators as a dichotomous decision, the model suggests the optimal number of integrators, i.e. systems, and individual part suppliers. We propose new measures for integration risk, which build upon current risk assessment practices. Robust optimisation is used to study the effect of uncertainty over baseline risk values. All approaches were tested using both randomly generated instances and real data from a large European OEM in the aerospace industry.

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.

Teses
supervisionadas

2022

Selecting fast-moving consumer goods product lines

Autor
Xavier António Reis Andrade

Instituição
UP-FEUP

2022

Tri-dimensional Reconstruction of Submerged Objects through an Active Eye-in-Hand Perception System

Autor
João Pedro da Silva Esteves

Instituição
UP-FEUP

2022

Visual Odometry System using Multi-Modal Information in Autonomous Driving Scenarios

Autor
Lucas Rebelo Agostinho

Instituição
UP-FEUP

2022

Digital Polar Transmitters for Emerging Wireless Communications

Autor
Rui Filipe de Pinho Gomes

Instituição
UP-FEUP

2022

Effects of vicarious and direct experience on tourists’ cognitive knowledge, affective reactions and behavioral outcomes regarding the destination: a schema-based intra-cultural comparison of chinese and Macau outbound tourists in europe

Autor
Jianjian Mou

Instituição
UP-FEP