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About

About

His main area of activity is Management Science/Operations Research. He develops and applies advanced analytical models and methods to help make better decisions, solving managerial problems in various domains (manufacturing, health, retail and mobility), with a special focus on Operations Management.

Associate Professor (with “Agregação”) at Industrial Engineering and Management, FEUP. Member of the Board at INESC TEC Technology and Science. Visiting Professor at University of São Paulo. Vice-Academic Director of IBM Center for Advanced Studies Portugal (IBM-CAS). Co-founder of INESC TEC spin-off LTPlabs  and of start-up Adjust Consulting (that was merged into Glintt HealthCare). Member of the board of Trustees ("conselho de curadores") of Fundação Belmiro de Azevedo.

Degree in Management and Industrial Engineering (5 years degree), FEUP. PhD in Industrial Engineering and Management, UP. Former researcher at Operations Research Center of Massachusetts Institute of Technology – MIT/ORC. Certified Analytics Professional from The Institute for Operations Research and the Management Sciences.

Interest
Topics
Details

Details

019
Publications

2019

Consistent Consolidation Strategies in Grocery Retail Distribution

Authors
Martins, S; Amorim, P; Almada Lobo, B;

Publication
Springer Proceedings in Mathematics and Statistics

Abstract
In the food retail sector, maintaining the food quality across the supply chain is of vital importance. The quality of the products is dependent on its storage and transportation conditions and this peculiarity increases the supply chain complexity relatively to other types of retailers. Actually, in this industry there are three types of food supply chains: frozen, chilled and ambient. Moreover, food retailers run different store formats, of different sizes, assortments and sales volume. In this study we research the trade-off between consolidating a range of products in order to perform direct deliveries to the stores versus performing separate delivery routes for products with different transportation requirements. A new consistency dimension is proposed regarding the periodicity that a consolidation strategy is implemented. The aim of this paper is to define a consolidation strategy for the delivery mode planning that allows to smooth the complexity of grocery retail operations. A three-step approach is proposed to tackle a real size problem in a case-study with a major Portuguese grocery retailer. By changing the consolidation strategy with a complete consistent plan the company could reach annual savings of around 4%. © 2019, Springer Nature Switzerland AG.

2019

Consistent vehicle routing problem with service level agreements: A case study in the pharmaceutical distribution sector

Authors
Campelo, P; Neves Moreira, F; Amorim, P; Almada Lobo, B;

Publication
European Journal of Operational Research

Abstract
In this paper, a mathematical model is developed to tackle a Consistent Vehicle Routing Problem, which considers customers with multiple daily deliveries and different service level agreements such as time windows, and release dates. In order to solve this problem, an instance size reduction algorithm and a mathematical programming based decomposition approach are developed. This solution approach is benchmarked against a commercial solver. Results indicate that the method solves instances of large size, enabling its application to real-life scenarios. A case study in a pharmaceutical distribution company is analyzed. Consistent routes are planned for several warehouses, comprising hundreds of orders. A simulation model evaluates the performance of the generated route plans. Significant improvements in terms of the total distance traveled and the total travel times are obtained when compared to the company's current planning process. © 2018 Elsevier B.V.

2019

Product-oriented time window assignment for a multi-compartment vehicle routing problem

Authors
Martins, S; Ostermeier, M; Amorim, P; Hübner, A; Almada-Lobo, B;

Publication
European Journal of Operational Research

Abstract

2018

A computational study of the general lot-sizing and scheduling model under demand uncertainty via robust and stochastic approaches

Authors
Alem, D; Curcio, E; Amorim, P; Almada Lobo, B;

Publication
COMPUTERS & OPERATIONS RESEARCH

Abstract
This paper presents an empirical assessment of the General Lot-Sizing and Scheduling Problem (GLSP) under demand uncertainty by means of a budget-uncertainty set robust optimization and a two-stage stochastic programming with recourse model. We have also developed a systematic procedure based on Monte Carlo simulation to compare both models in terms of protection against uncertainty and computational tractability. The extensive computational experiments cover different instances characteristics, a considerable number of combinations between budgets of uncertainty and variability levels for the robust optimization model, as well as an increasing number of scenarios and probability distribution functions for the stochastic programming model. Furthermore, we have devised some guidelines for decision-makers to evaluate a priori the most suitable uncertainty modeling approach according to their preferences.

2018

Forecasting the medical workforce: a stochastic agent-based simulation approach

Authors
Lopes, MA; Almeida, AS; Almada Lobo, B;

Publication
Health Care Management Science

Abstract
Starting in the 50s, healthcare workforce planning became a major concern for researchers and policy makers, since an imbalance of health professionals may create a serious insufficiency in the health system, and eventually lead to avoidable patient deaths. As such, methodologies and techniques have evolved significantly throughout the years, and simulation, in particular system dynamics, has been used broadly. However, tools such as stochastic agent-based simulation offer additional advantages for conducting forecasts, making it straightforward to incorporate microeconomic foundations and behavior rules into the agents. Surprisingly, we found no application of agent-based simulation to healthcare workforce planning above the hospital level. In this paper we develop a stochastic agent-based simulation model to forecast the supply of physicians and apply it to the Portuguese physician workforce. Moreover, we study the effect of variability in key input parameters using Monte Carlo simulation, concluding that small deviations in emigration or dropout rates may originate disparate forecasts. We also present different scenarios reflecting opposing policy directions and quantify their effect using the model. Finally, we perform an analysis of the impact of existing demographic projections on the demand for healthcare services. Results suggest that despite a declining population there may not be enough physicians to deliver all the care an ageing population may require. Such conclusion challenges anecdotal evidence of a surplus of physicians, supported mainly by the observation that Portugal has more physicians than the EU average. © 2016 Springer Science+Business Media New York

Supervised
thesis

2017

Master Production Planning for the Glass Container Industry: Scenario Analysis

Author
Filipe Fernandes Rocha

Institution
UP-FEUP

2017

Optimization of Returnable Packaging Flows Planning

Author
Maria Manuel Pires Afonso dos Santos

Institution
UP-FEUP

2017

Raw Materials Sourcing Optimization in the Tire Industry

Author
Marta Ribeiro Vaz da Silveira

Institution
UP-FEUP

2016

Integrating Lot-Sizing Problems Under Uncertainty

Author
Eduardo Ferian Curcio

Institution
UP-FEUP

2016

The impact of servitization on the performance of manufacturing firms over time: An empirical investigation in the elevator industry

Author
Miguel Leichsenring Franco

Institution
UP-FEUP