Publications

Publications by CESE

2025

Socio-Technical AI Maturity in Supply Chains: Insights from the Pulp and Paper Sector

Authors
Fernanda Freitas; Ricardo Zimmermann; Gaudencio Freires; Fabio Couto; Cristiano Fontes; António Lucas Soares; Gustavo Dalmarco; Donna Rhodes; Jorão Gomes;

Publication
IFIP advances in information and communication technology

Abstract

2025

Generative AI as a Catalyst for Collaborative Knowledge Management: Impacts Across Individual, Intra, and Inter-organizational Levels

Authors
Silva, RR; Silva, HD; Soares, AL;

Publication
IFIP Advances in Information and Communication Technology - Hybrid Human-AI Collaborative Networks

Abstract

2025

A Human-Centric Agent Architecture for Hybrid Industrial Collaboration in Industry 5.0

Authors
Sousa, J; Oliveira, F; Carneiro, D; Soares, A; Silva, B;

Publication
IFIP Advances in Information and Communication Technology - Hybrid Human-AI Collaborative Networks

Abstract

2025

Collaborating with Algorithms: AI for Collaborative Supply Chain Management

Authors
Fabio Couto; Mariana Curado Malta; António Lucas Soares;

Publication
IFIP advances in information and communication technology

Abstract

2025

Comparative Analysis of Simulated Annealing and Tabu Search for Parallel Machine Scheduling

Authors
Mota, A; Ávila, P; Bastos, J; Roque, AC; Pires, A;

Publication
Procedia Computer Science

Abstract
This paper compares the performance of Simulated Annealing and Tabu Search meta-heuristics in addressing a parallel machine scheduling problem aimed at minimizing weighted earliness, tardiness, total flowtime, and machine deterioration costs-a multi-objective optimization problem. The problem is transformed into a single-objective problem using weighting and weighting relative distance methods. Four scenarios, varying in the number of jobs and machines, are created to evaluate these metaheuristics. Computational experiments indicate that Simulated Annealing consistently yields superior solutions compared to Tabu Search in scenarios with lower dimensions despite longer run times. Conversely, Tabu Search performs better in higher-dimensional scenarios. Furthermore, it is observed that solutions generated by different weighting methods exhibit similar performance. © 2025 The Author(s).

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2025

Boosting Governance-Centric Digital Product Passports Through Traceability in Footwear Industry

Authors
Moço, H; Sousa, C; Ferreira, R; Pinto, P; Pereira, C; Diogo, R;

Publication
INNOVATIVE INTELLIGENT INDUSTRIAL PRODUCTION AND LOGISTICS, IN4PL 2024, PT II

Abstract
Since supply chains have become complex and tracking a product's journey, from raw materials to the end of it's life has become more difficult. Consumers are demanding greater transparency about the materials origins and environmental impact of the products they buy. These new requirements, togeher with European Commission Green Deal strategy, lead to the concept of digital product passport (DPP). DPP could be seen as an instrument to boost circularity, however the DPP architecture and governance model still undefined and unclear. Data Governance in the context of the DPP acts as the backbone for ensuring accurate and reliable data within these passports or data models, leading to flawless traceability. This article approaches the DPPs and it's governance challenges, explaining how they function as digital repositories for a product's life cycle information and the concept of Data Governance. By understanding how these two concepts work together, we will explore a short use case within the footwear industry to show how DPP governance architecture might work in a distributed environment.

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