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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
Systems Engineering and Management

TestBed 5G: INESC TEC in half of the pilots that aim to boost the manufacturing industry

INESC TEC’s Industry and Innovation Laboratory (iiLab) has already received six of the 12 planned pilots. The demonstrations aim to provide industrial solutions with different operating and coordination features.  

29th October 2024

Systems Engineering and Management

Sorting, organising, palletising: INESC TEC technology paving the way to an optimised supply chain

The Institute contributed to a solution that reduces manual efforts and ensures a more flexible supply chain. This involvement was “fundamental”, stemming from the ongoing progress of the PRODUTECH R3 mobilising agenda.  

29th October 2024

Drones, automation and sensing: here are INESC TEC’s solutions to the challenges of the wine sector

INESC TEC researchers led discussions on innovative solutions for vineyards at an event that brought together companies, universities and players in the sector.  

24th October 2024

Systems Engineering and Management

INESC TEC researcher warns companies about the quality of data generated through AI in a paper published by MIT management journal

Could the increasing interest in language models, like ChatGPT, be diverting resources away from companies to adopt advanced analytics practices that truly support smart decisions? Pedro Amorim, INESC TEC researcher, and João Alves (from INESC TEC LTPLabs spin-off) believe so. In a paper published in MIT Sloan Management Review, they warn about the quality and unpredictability of data generated solely from generative language models - despite advocating for more investment in Artificial Intelligence (AI) that incorporates these models with advanced analysis (with concrete reasons provided).

25th June 2024

This technology aims to make cities more accessible for everyone - and earned a recognition for an INESC TEC researcher

INESC TEC researcher Marta Campos Ferreira participated in the development of a prototype that seeks to improve the experiences of people with reduced mobility in cities – and make them more inclusive. The new solution featured at an international conference, and the researcher's work was acknowledged. Now, the goal is for the solution to reach everyone through an application.

17th May 2024

001

Featured Projects

PFAI4_5eD

Programa de Formação Avançada Industria 4 - 5a edição

2024-2024

Team
Publications

CEGI Publications

View all Publications

2025

Local stability in kidney exchange programs

Authors
Baratto, M; Crama, Y; Pedroso, JP; Viana, A;

Publication
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH

Abstract
When each patient of a kidney exchange program has a preference ranking over its set of compatible donors, questions naturally arise surrounding the stability of the proposed exchanges. We extend recent work on stable exchanges by introducing and underlining the relevance of a new concept of locally stable, or L-stable, exchanges. We show that locally stable exchanges in a compatibility digraph are exactly the so-called local kernels (L-kernels) of an associated blocking digraph (whereas the stable exchanges are the kernels of the blocking digraph), and we prove that finding a nonempty L-kernel in an arbitrary digraph is NP-complete. Based on these insights, we propose several integer programming formulations for computing an L-stable exchange of maximum size. We conduct numerical experiments to assess the quality of our formulations and to compare the size of maximum L-stable exchanges with the size of maximum stable exchanges. It turns out that nonempty L-stable exchanges frequently exist in digraphs which do not have any stable exchange. All the above results and observations carry over when the concept of (locally) stable exchanges is extended to the concept of (locally) strongly stable exchanges.

2025

Predicting demand for new products in fashion retailing using censored data

Authors
Sousa, MS; Loureiro, ALD; Miguéis, VL;

Publication
EXPERT SYSTEMS WITH APPLICATIONS

Abstract
In today's highly competitive fashion retail market, it is crucial to have accurate demand forecasting systems, namely for new products. Many experts have used machine learning techniques to forecast product sales. However, sales that do not happen due to lack of product availability are often ignored, resulting in censored demand and service levels that are lower than expected. Motivated by the relevance of this issue, we developed a two-stage approach to forecast the demand for new products in the fashion retail industry. In the first stage, we compared four methods of transforming historical sales into historical demand for products already commercialized. Three methods used sales-weighted averages to estimate demand on the days with stock-outs, while the fourth method employed an Expectation-Maximization (EM) algorithm to account for potential substitute products affected by stock-outs of preferred products. We then evaluated the performance of these methods and selected the most accurate one for calculating the primary demand for these historical products. In the second stage, we predicted the demand for the products of the following collection using Random Forest, Deep Neural Networks, and Support Vector Regression algorithms. In addition, we applied a model that consisted of weighting the demands previously calculated for the products of past collections that were most similar to the new products. We validated the proposed methodology using a European fashion retailer case study. The results revealed that the method using the Expectation-Maximization algorithm had the highest potential, followed by the Random Forest algorithm. We believe that this approach will lead to more assertive and better-aligned decisions in production management.

2025

Emerging technologies for supporting patients during Hemodialysis: A scoping review

Authors
Martins, AR; Ferreira, MC; Fernandes, CS;

Publication
International Journal of Medical Informatics

Abstract

2025

Emerging technologies for supporting patients during Hemodialysis: A scoping review

Authors
Martins, AR; Ferreira, MC; Fernandes, CS;

Publication
INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS

Abstract
Purpose:To synthesizethe availableevidenceaboutthe use of HealthInformationTechnology(HIT)to supportpatientsduringhemodialysis.Methods:TheJoannaBriggsInstitute's methodologicalguidelinesfor scopingreviewsandthe PRISMA-ScRchecklistwereemployed.BibliographicsearchesacrossMEDLINE (R), CINAHL (R), PsychologyandBehavioralSciencesCollection,Scopus,MedicLatina,and Cochraneyielded932 records.Results:Eighteenstudiespublishedbetween2003and2023wereincluded.Theyexploreda rangeof HITs,includingvirtualreality,exergames,websites,and mobileapplications,all specificallydevelopedfor use duringthe intradialyticperiod.Conclusion:Thisstudyhighlightsthe HITsdevelopedfor use duringhemodialysistreatment,supportingphysicalexercise,diseasemanagement,and enhancementof self-efficacyand self-care.

2025

A GRASP-based multi-objective approach for the tuna purse seine fishing fleet routing problem

Authors
Granado, I; Silva, E; Carravilla, MA; Oliveira, JF; Hernando, L; Fernandes-Salvador, JA;

Publication
COMPUTERS & OPERATIONS RESEARCH

Abstract
Nowadays, the world's fishing fleet uses 20% more fuel to catch the same amount offish compared to 30 years ago. Addressing this negative environmental and economic performance is crucial due to stricter emission regulations, rising fuel costs, and predicted declines in fish biomass and body sizes due to climate change. Investment in more efficient engines, larger ships and better fuel has been the main response, but this is only feasible in the long term at high infrastructure cost. An alternative is to optimize operations such as the routing of a fleet, which is an extremely complex problem due to its dynamic (time-dependent) moving target characteristics. To date, no other scientific work has approached this problem in its full complexity, i.e., as a dynamic vehicle routing problem with multiple time windows and moving targets. In this paper, two bi-objective mixed linear integer programming (MIP) models are presented, one for the static variant and another for the time-dependent variant. The bi-objective approaches allow to trade off the economic (e.g., probability of high catches) and environmental (e.g., fuel consumption) objectives. To overcome the limitations of exact solutions of the MIP models, a greedy randomized adaptive search procedure for the multi-objective problem (MO-GRASP) is proposed. The computational experiments demonstrate the good performance of the MO-GRASP algorithm with clearly different results when the importance of each objective is varied. In addition, computational experiments conducted on historical data prove the feasibility of applying the MO-GRASP algorithm in a real context and explore the benefits of joint planning (collaborative approach) compared to a non-collaborative strategy. Collaborative approaches enable the definition of better routes that may select slightly worse fishing and planting areas (2.9%), but in exchange fora significant reduction in fuel consumption (17.3%) and time at sea (10.1%) compared to non-collaborative strategies. The final experiment examines the importance of the collaborative approach when the number of available drifting fishing aggregation devices (dFADs) per vessel is reduced.

Facts & Figures

13Academic Staff

2020

56Researchers

2016

2Book Chapters

2020