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Facts & Numbers
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Presentation

Industrial Engineering and Management

The centre is an international reference in business analytics through decision support systems for service and operations management, contributing also in service design, performance assessment and asset management.

Our core areas of application include Mobility/Transports, Retail/Industry and Healthcare, also with significant contributions in the Energy Sector and a strengthened collaboration with the Centre for Power and Energy Systems.

In the latest years, CEGI substantially contribute to Industry 4.0 initiatives (improving scheduling rules based on the additional information available in manufacturing systems).

Latest News
Computer Science

Technology that reduces treatment time for cancer patients wins digital innovation award

The Gentil – Text Mining project won the Portugal Digital Awards in the Best Future of Work Project category, which acknowledges the best initiative related to employees' productivity and effectiveness.

06th January 2022

Industrial and Systems Engineering

INESC TEC leads project to prevent food waste

INESC TEC is leading a project that aims to tackle food waste, by improving operational efficiency in the food value chain. The project, called Be Fresh – Integrating Consumer Behavior to Improve Food Value Chains, falls in with three of the Sustainable Development Goals (SDGs), namely ending hunger, promoting sustained, inclusive and sustainable economic growth, and ensuring sustainable consumption and production patterns. INESC TEC's new project will start in January 2022.

15th December 2021

Industrial and Systems Engineering

INESC TEC researchers receive research and teaching awards

Four INESC TEC researchers in the field of industrial management engineering received research and teaching awards by the Portuguese Association of Operational Research (APDIO) and by the School of Engineering of the University of Minho (EEUM), respectively.

23rd November 2021

INESC TEC participates in project to promote forestry

INESC TEC is part of the consortium of the rePLANT project, led by the collaborative laboratory ForestWISE, which aims to create new technologies and services, mostly supported by digital technologies, in the fields of integrated forest and fire management.

26th April 2021

Industrial and Systems Engineering

INESC TEC aims to make Artificial Intelligence more explainable, transparent and reliable

The TRUST-AI project, coordinated by INESC TEC’s Centre for Industrial Engineering and Management (CEGI) seeks to explain AI systems, making them more transparent and reliable.

09th March 2021

Interest Topics
088

Featured Projects

Produtech R3

Agenda Mobilizadora da Fileira das Tecnologias de Produção para a Reindustrialização

2022-2025

PFAI4_3ed

Programa de Formação Avançada Industria 4 - 3a edição

2022-2022

FORM_I40

Formação Indústria 4.0

2022-2022

BestOrder3

Gestão de inventário de farmácias comunitárias

2022-2023

BeFresh

On incorporating consumer behaviour into the supply chain planning of fresh products

2022-2024

DRIVEN

Decision Rules made Interpretable, Verifiable and Effective for governing Farfetch Network

2021-2022

SolIM62010

Intelligent marketing solutions

2021-2022

BEST_ORDER_II

Gestão de inventário nas farmácias portuguesas - Fase II

2021-2022

EUSCORES

EUropean - Scalable and Complementary Offshore Renewable Energy Sources

2021-2025

AI4PV

Artificial Intelligence for Operation and Maintenance of PV Plants

2021-2023

DIGITALCER

Digital Energy Platform for Energy Communities

2021-2023

SmartPV

Desenvolvimento de plataforma de gestão de ativos PV através de prevenção inteligente de falhas

2021-2023

TRUSTAI

Transparent, Reliable and Unbiased Smart Tool for AI

2020-2025

BestOrder

Gestão de inventário nas farmácias portuguesas

2020-2021

PFAI4.0

Programa de Formação Avançada Industria 4.0

2020-2021

FPP2

Fleet Planning and Pricing

2020-2020

TRF4p0

Digital revolution of power transformers

2020-2023

PLASMA 4 COVID

Agilização da colheita de plasma convalescente

2020-2021

Replant

Implantação de estratégias colaborativas para a gestão integrada da floresta e do fogo

2020-2023

FPP

Fleet Planning and Pricing

2020-2020

MINE4HEALTH

Text mining e clinical decision-making

2020-2021

WINDEXT

Advanced maintenance, lifetime extension and repowering of wind farms supported by advanced digital tools

2020-2022

CrossLOG

AUTOMATIC MIXED-PALLETIZING FOR CROSS-DOCKING LOGISTICS CENTERS

2019-2022

POCITYF

A POsitive Energy CITY Transformation Framework

2019-2024

XFLEX_HIDRO

Hydropower Extending Power System Flexibility

2019-2023

T4CDTKC

Training 4 Cotec, Digital Transformation Knowledge Challenge - Elaboração de Programa de Formação “CONHECER E COMPREENDER O DESAFIO DAS TECNOLOGIAS DE TRANSFORMAÇÃO DIGITAL”

2019-2021

ENCKEP

European Network for Collaboration on Kidney Exchange Programmes

2019-2021

OCP_STOCK

Gestão de inventário nas farmácias portuguesas

2019-2020

ValProduct

Estudo sobre o impacto das validades dos produtos nos contratos

2019-2019

PortoAmbiente

ESTUDO SOBRE A RECOLHA SELETIVA DE RESÍDUOS URBANOS COMERCIAIS

2019-2020

RM20

Car Rental Revenue Management 2.0

2019-2020

FIN-TECH

A FINancial supervision and TECHnology compliance training programme

2019-2021

VAR

Avaliação de risco das válvulas de rede primária : vida útil restante e condições de operação

2019-2019

OpenInnoTrain

Research Translation and Applied Knowledge Exchange in Practice through University-Industry-Cooperation

2019-2024

DoubleChain

Supporting ubiquitous and fully decentralized supply chain operations through blockchain technology

2018-2020

LASTMILE

Rethinking last-mile delivery through crowdsourcing

2018-2022

SiuSMS

Smart (inter)urban shared mobility systems: integrating pricing and fleet management for a sustainable mobility planning future

2018-2022

DeltaC&P

Uncertainty in cutting and packing problems: robust planning and optimized replanning in manufacturing and transportation

2018-2022

opti-MOVES

Quality management of intermodal public transport services: diagnosis and optimization

2018-2022

KnowlogisII

Ferramenta de apoio à logística de farmácias hospitalares

2018-2020

ASAP

Airport slot allocation processes: advances in current guidelines and practices

2018-2022

BEEF

Estudo da gestão de produção, inventário e compras através de métodos analíticos

2018-2019

Tec-FEL

Logistics 4.0: Technologies for flexible and eco-efficient logistics

2018-2021

HIP

Heath Index for Power Transformers

2018-2018

MANU-SQUARE

MANUfacturing ecoSystem of QUAlified Resources Exchange

2018-2021

HEAD

Heath index for assets of the distribuition network

2018-2022

WinePallet

Otimização do sistema de paletização

2017-2017

UPGASII

Gestão de ativos na rede de distribuição de gás (Fase II)

2017-2018

ANPCARE

Os cuidados de enfermagem especializados como resposta à evolução das necessidades em cuidados de saúde

2017-2017

KnowLOGIS

KnowLOGIS - Expertise in Healthcare Logistics

2017-2019

PricingSdL

Sistema de Apoio à Decisão para a definição de preços

2017-2017

InteGrid

Demonstration of INTElligent grid technologies for renewables INTEgration and INTEractive consumer participation enabling INTEroperable market solutions and INTErconnected stakeholders

2017-2020

Path

Políticas de manutenção preditiva apoiadas na fiabilidade de transformadores

2017-2017

SIMOPT

Simulação e Optimização na Distribuição Alimentar

2017-2017

DM4Manufacturing

Aligning Manufacturing Decision Making with Advanced Manufacturing Technologies

2016-2021

Atena

Saber para intervir: observatório para a educação

2016-2019

EasyFlow

Collaborative and efficient logistics towards more sustainable forest suplly chain

2016-2019

HHRPLAN

Foresight and decision support tools for improved healthcare workforce planning and policy analysis

2016-2018

mKEP

mKEP - Models and optimisation algorithms for multicountry kidney exchange programs

2016-2019

CORAL-TOOLS

CORAL – Sustainable Ocean Exploitation: Tools and Sensors

2016-2018

LTP

Consultoria em data minning e otimização em diferentes problemas abordados pela LTP

2016-2017

UpGas

Gestão de ativos na rede de distribuição de gás

2015-2016

iMAN

iMAN - Intelligence for advanced Manufacturing systems

2015-2019

SMILES

SMILES - Smart, Mobile, Intelligent and Large scale Sensing and analytics

2015-2019

HIDRO

Desenvolvimento de um modelo integrado de engenharia de fiabilidade

2015-2016

RosaEvolution

Melhoria de eficiência do Sistema Rosa Evolution com o objetivo de reduzir as não conformidades provocadas pelo TCA

2015-2016

BestWare

Dimensionamento de armazéns integrados em lojas de retalho alimentar

2015-2017

ShortPath

Análise de processos de distribuição com vista à formulação de propostas de melhoria ao processo de distribuição atual

2015-2016

Rent-a-Car-Pricing

Conceção e implementação de um Sistema de Apoio às Decisões de Pricing

2015-2015

UPGRID

Real proven solutions to enable active demand and distributed generation flexible integration, through a fully controllable LOW Voltage and medium voltage distribution grid

2015-2017

ReliabilityEng2

Reliability Engineering for Wind Turbine Generators - Phase II

2014-2015

Supply_Chain

Melhoramento do desempenho da cadeia de fornecimento e na organização de recursos

2014-2016

ShortCut

Organização e localização dos produtos nas prateleiras e no mezanino do armazém principal

2014-2015

StorePacks

Definição de produtos StorePack, dos armazéns até às lojas

2014-2015

SuperStore

Replenishment System for on-line SuperStore

2014-2014

Mailing

Mailing optimisation: Quantitative Methods for Coupon Allocation

2014-2014

PromoStock

Retail Promotional Replenishment and Forecasting

2014-2014

WholeChain

Whole Chain: Quantitative Framework for Perishable Food Supply Chain Management

2014-2015

ReliabilityEng

Reliability Engineering for Wind Turbine Generators

2014-2014

PSS-DESIGN

Estudo e desenvolvimento de metodologias para sistemas e produtos e serviços no âmbito do projeto INTELLAB II

2014-2015

MEDSC

Supply chain of a pharmaceutical grocery

2014-2014

PTGlass

Tactical integrated production and distribution planning at glass container industry

2013-2014

SmartManufacturing

Smart Manufacturing and Logistics

2013-2015

SAGRH

Advanced System for Medical Human Resources Management

2012-2014

GESTAO_FLUXOS

Long-haul freight distribution optimisation

2012-2014

StableCargo

Cargo stability analysis in container transportation: a hybrid optimisation - heuristics framework

2012-2015

SADRH

Staff allocation and scheduling optimisation algorithms

2012-2014

KEP

New models to enhance kidney transplants

2011-2014

Team
Publications

CEGI Publications

View all Publications

2022

2-echelon lastmile delivery with lockers and occasional couriers

Authors
Dos Santos, AG; Viana, A; Pedroso, JP;

Publication
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW

Abstract
We propose a new approach for the lastmile delivery problem where, besides serving as collecting points of orders for customers, parcel lockers are also used as transshipment nodes in a 2-echelon delivery system. Moreover, we consider that a customer (occasional courier) visiting a locker may accept a compensation to make a delivery to another customer on their regular traveling path. The proposed shared use of the locker facilities - by customers that prefer to self-pick up their orders, and also as a transfer deposit for customers that prefer home delivery - will contribute to better usage of an already available storage capacity. Furthermore, the use of occasional couriers (OCs) brings an extra layer of flexibility to the delivery process and may positively contribute to achieving some environmental goals: although non-consolidation of deliveries may, at first sight, seem negative, by only considering OCs that would go to the locker independently of making or not a delivery on their way home, and their selection being constrained by a maximum detour, the carbon footprint can be potentially reduced when compared to that of dedicated vehicles. We present a mixed-integer linear programming formulation for the problem that integrates three delivery options - depot to locker, depot to locker followed by final delivery by a professional fleet, and depot to locker followed by final delivery by an OC. Furthermore, to assess the impact of OCs' no show on the delivery process, we extend the formulation to re-schedule the delivery of previous undelivered parcels, and analyze the impact of different no-show rates. Thorough computational experiments show that the use of OCs has a positive impact both on the delivery cost and on the total distance traveled by the dedicated fleets. Experiments also show that the negative impact of no-shows may be reduced by using lockers with higher capacities.

2022

The Sea Exploration Problem Revisited

Authors
Dionisio, J; dos Santos, D; Pedroso, JP;

Publication
MACHINE LEARNING, OPTIMIZATION, AND DATA SCIENCE (LOD 2021), PT I

Abstract
Sea exploration is important for countries with large areas in the ocean under their control, since in the future it may be possible to exploit some of the resources in the seafloor. The sea exploration problem was presented by Pedroso et al. [13] (unpublished); we maintain most of the paper's structure, to provide the needed theoretical background and context. In the sea exploration problem, the aim is to schedule the expedition of a ship for collecting information about the resources on the seafloor. The goal is to collect data by probing on a set of carefully chosen locations, so that the information available is optimally enriched. This problem has similarities with the orienteering problem, where the aim is to plan a time-limited trip for visiting a set of vertices, collecting a prize at each of them, in such a way that the total value collected is maximum. In our problem, the score at each vertex is associated with an estimation of the level of the resource on the given surface, which is done by regression using Gaussian processes. Hence, there is a correlation among scores on the selected vertices; this is the first difference with respect to the standard orienteering problem. The second difference is the location of each vertex, which in our problem is a freely chosen point on a given surface. Results on a benchmark test set are presented and analyzed, confirming the merit of the approach proposed. In this paper, additional methods are presented, along with a small topological result and subsequent proof of the convergence of these same methods to the optimal solution, when we have instant access to the ground truth and the underlying function is piecewise continuous.

2022

Theories, constructs, and methodologies to study COVID-19 in the service industries

Authors
Cambra-Fierro, J; Gao, L; Melero-Polo, I; Patricio, L;

Publication
SERVICE INDUSTRIES JOURNAL

Abstract
Despite the wide variety of literature on the impact of the COVID-19 pandemic in the service industry, there is still a lack of an integrated systematized view of these multiple impacts. This study contributes to service research by identifying a variety of academic and managerial perspectives about the influence of COVID-19. We pay attention to the service industry, but with an especial focus on the tourism and hospitality industries, which have been more severely affected. This paper presents two multi-approach studies blending a systematic literature review (SLR) and a focus group methodology. Hence, it integrates and synthesizes the main results of the two studies considered to assist researchers and practitioners. It offers a complete overview of the state of the art and identifies three key service trends that have been accelerated by COVID-19: (1) the increasingly digital and autonomous customer; (2) the growing potential of data-driven services versus privacy concerns, and (3) the evolution from firm-centric to customer-centric and networked business models. Finally, this study provides relevant theoretical implications where we suggest relevant theories, constructs, and methodologies for future research to advance the current knowledge, and useful guidelines for business managers to better understand how to respond to market changes.

2022

To Use or Not to Use? Investigating What Drives Tourists to Use Mobile Ticketing Services in Tourism

Authors
Ferreira, MC; Oliveira, M; Dias, TG;

Publication
SUSTAINABILITY

Abstract
The advantages associated with mobile ticketing solutions are undeniable; however, most of these solutions are designed for the local population without taking into account the specific needs of tourists. Therefore, this study fills an important research gap in the literature by assessing the adoption drivers of mobile ticketing services by tourists and pointing out possible directions to the design of such services. The proposed model includes constructs of the technology acceptance model (TAM), diffusion of innovations (DOI) theory, and others widely disseminated in the literature on mobile payments, such as mobility. The model was empirically tested through an online survey, and Structural Equation Modeling (SEM) was applied to analyze the data. The results show that the intention of tourists to use mobile ticketing services is positively affected by the perceived usefulness and mobility. The survey findings also describe additional services that respondents value in a mobile ticket service for tourists, both in normal and in pandemic contexts, useful to shape future mobile ticketing solutions for tourists.

2022

Traffic State Prediction Using One-Dimensional Convolution Neural Networks and Long Short-Term Memory

Authors
Reza, S; Ferreira, MC; Machado, JJM; Tavares, JMRS;

Publication
APPLIED SCIENCES-BASEL

Abstract
Traffic prediction is a vitally important keystone of an intelligent transportation system (ITS). It aims to improve travel route selection, reduce overall carbon emissions, mitigate congestion, and enhance safety. However, efficiently modelling traffic flow is challenging due to its dynamic and non-linear behaviour. With the availability of a vast number of data samples, deep neural network-based models are best suited to solve these challenges. However, conventional network-based models lack robustness and accuracy because of their incapability to capture traffic's spatial and temporal correlations. Besides, they usually require data from adjacent roads to achieve accurate predictions. Hence, this article presents a one-dimensional (1D) convolution neural network (CNN) and long short-term memory (LSTM)-based traffic state prediction model, which was evaluated using the Zenodo and PeMS datasets. The model used three stacked layers of 1D CNN, and LSTM with a logarithmic hyperbolic cosine loss function. The 1D CNN layers extract the features from the data, and the goodness of the LSTM is used to remember the past events to leverage them for the learnt features for traffic state prediction. A comparative performance analysis of the proposed model against support vector regression, standard LSTM, gated recurrent units (GRUs), and CNN and GRU-based models under the same conditions is also presented. The results demonstrate very encouraging performance of the proposed model, improving the mean absolute error, root mean squared error, mean percentage absolute error, and coefficient of determination scores by a mean of 16.97%, 52.1%, 54.15%, and 7.87%, respectively, relative to the baselines under comparison.

Supervised Theses

2021

Advanced methodologies for the diagnosis of agronomic processes based on systems biology forprecision agriculture

Author
Renan Tosin

Institution
UP-FCUP

2021

Early detection and identification of plant diseases caused by bacteria based on proximal sensingfrom a precision agriculture perspective

Author
Mafalda Alexandra Reis Pereira

Institution
UP-FCUP

2021

Semantic Measures in Large Semantic Graphs

Author
André Fernandes dos Santos

Institution
UP-FCUP

2021

A dense and high throughput WLAN system using emerging Light Communications technology

Author
André da Silva Reis

Institution
UP-FEUP

2021

Jogos Sérios na Terceira Idade: Aprendizagem de comportamentos seguros e boas práticas na Web

Author
Iolanda Sofia dos Santos Bernardino

Institution
UTAD

Facts & Figures

9Proceedings in indexed conferences

2020

2Book Chapters

2020

13Academic Staff

2020