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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

016
Publications

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.

2017

Improving convolutional neural network design via variable neighborhood search

Authors
Araújo, T; Aresta, G; Almada Lobo, B; Mendonça, AM; Campilho, A;

Publication
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Abstract
An unsupervised method for convolutional neural network (CNN) architecture design is proposed. The method relies on a variable neighborhood search-based approach for finding CNN architectures and hyperparameter values that improve classification performance. For this purpose, t-Distributed Stochastic Neighbor Embedding (t-SNE) is applied to effectively represent the solution space in 2D. Then, k-Means clustering divides this representation space having in account the relative distance between neighbors. The algorithm is tested in the CIFAR-10 image dataset. The obtained solution improves the CNN validation loss by over 15% and the respective accuracy by 5%. Moreover, the network shows higher predictive power and robustness, validating our method for the optimization of CNN design. © Springer International Publishing AG 2017.

2017

Decentralized Vs. Centralized Sequencing in a Complex Job-Shop Scheduling

Authors
Mehrsai, A; Figueira, G; Santos, N; Amorim, P; Almada Lobo, B;

Publication
IFIP Advances in Information and Communication Technology

Abstract
Allocation of jobs to machines and subsequent sequencing each machine is known as job scheduling problem. Classically, both operations are done in a centralized and static/offline structure, considering some assumptions about the jobs and machining environment. Today, with the advent of Industry 4.0, the need to incorporate real-time data in the scheduling decision process is clear and facilitated. Recently, several studies have been conducted on the collection and application of distributed data in real-time of operations, e.g., job scheduling and control. In practice, pure distribution and decentralization is not yet fully realizable because of e.g., transformation complexity and classical resistance to change. This paper studies a combination of decentralized sequencing and central optimum allocation in a lithography job-shop problem. It compares the level of applicability of two decentralized algorithms against the central scheduling. The results show better relative performance of sequencing in stochastic cases. © IFIP International Federation for Information Processing 2017.

2017

An optimization-simulation approach to the network redesign problem of pharmaceutical wholesalers

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

Publication
COMPUTERS & INDUSTRIAL ENGINEERING

Abstract
The pharmaceutical industry operates in a very competitive and regulated market The increased pressure of pharmacies to order fewer products and to receive them more frequently is overcharging the pharmaceutical's distribution network Furthermore, the tight margins and the continuous growth of generic drugs consumption are pressing wholesalers to optimize their supply chains. In order to survive, wholesalers are rethinking their strategies to increase competitiveness. This paper proposes an optimization-simulation approach to address the wholesalers network redesign problem, trading off the operational costs and customer service level. Firstly, at a strategic-tactical level, the supply chain network redesign decisions are optimized via a mixed integer programming model. Here, the number, location, function and capacity of the warehouses, the allocation of customers to the warehouses and the capacity and function of the distribution channels are defined. Secondly, at an operation level, the solution found is evaluated by means of a discrete event simulation model to assess the impact of the redesign in the wholesaler's daily activities. Computational results on a pharmaceutical wholesaler case-study are discussed and the benefits of this solution approach exposed.

2017

Tactical production and distribution planning with dependency issues on the production process

Authors
Wei, WC; Guimaraes, L; Amorim, P; Almada Lobo, B;

Publication
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE

Abstract
Tactical production-distribution "planning models have attracted a great deal of attention in the past decades. In these models, production and distribution decisions are considered simultaneously such that the combined plans are more advantageous than the plans resolved in a hierarchical planning process. We consider a two-stage production process, where in the first stage raw materials are transformed into continuous resources that feed the discrete production of end products in the second stage. Moreover, the setup times and costs of resources depend on the sequence in which they are processed in the first stage. The minimum scheduling unit is the product family which consists of products sharing common resources and manufacturing processes. Based on different mathematical modelling approaches to the production in the first stage, we develop a sequence-oriented formulation and a product-oriented formulation, and propose decomposition-based heuristics to solve this problem efficiently. By considering these dependencies arising in practical production processes, our model can be applied to various industrial cases, such as the beverage industry or the steel industry. Computation tests on instances from an industrial application are provided at the end of the paper.

Supervised
thesis

2016

Assessing and planning for the future needs of the health care workforce

Author
Mário Filipe Amorim Faria de Oliveira Lopes

Institution
UP-FEUP

2016

Retailer delivery mode planning: Analyzing the multiple ways to supply brick-and-mortar stores

Author
Sara Sofia Baltazar Martins

Institution
UP-FEUP

2016

Definição do modelo de aprovisionamento de matérias-primas

Author
Francisco Jorge Freitas Salazar de Oliveira

Institution
UP-FEUP

2016

Redução do consumo de vidro nas linhas de enchimento de uma unidade cervejeira

Author
Miguel Ângelo da Silva Duarte

Institution
UP-FEUP

2016

Otimização e Standardização de Procedimentos em Linhas de Enchimento do Barril

Author
Nuno Miguel Moreira de Sousa

Institution
UP-FEUP