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).

Abstract
The recent past has shown that many companies stressed from the competition, have reduced manufacturing costs as well implemented sustainable practices as much as possible. And yet this effort has proved to be insufficient. This reality is forcing the companies and managers to address the problem of competitiveness and sustainability in a holistic way, by considering the entire supply chain. Due to this pressure from supply chain stakeholders to a comprehensive sustainability assessment of the entire network, extended “performance metrics” are required not only on the economic value of a business, but also in its environmental and social impacts. Increasing numbers of organizations report a massive volume of data, with low consistency and high variability in data quality, and a dispersion of indicators, making it necessary to develop and implement new approaches for Supply Cain Management (SCM) sustainable performance assessment. This paper focuses on this topic, presenting a new approach for performance and risk assessment within dynamic supply chain networks, supported in a new and comprehensive Sustainability Assessment Framework (SAF).

Abstract
Este livro é o resultado do arranjo e compilação de textos didáticos produzidos ou adaptados pelos seus autores para apoio a unidades curriculares dos mestrados em Engenharia Mecânica - Gestão Industrial e Engenharia Eletrotécnica e Computadores – Sistemas de Planeamento Industrial, do Instituto Superior de Engenharia do Politécnico do Porto. Esses textos foram revistos e reorganizados, com vista, não só a manterem a função original de ajuda à formação de estudantes afetos a esta área do conhecimento, como também a constituírem uma referência de conhecimentos para quem deseje iniciar-se nestes temas; procuram ainda ser uma base de consulta e informação para engenheiros ou outros profissionais com funções na gestão da produção. O livro percorre os marcos mais significativos da trajetória histórica da gestão da produção, com particular foco no planeamento e controlo da produção, procurando interpretar e tornar compreensível a sua evolução, e relevando, sempre que oportuno, a influência da tecnologia nos modelos de gestão, e sua interligação. Começa por uma referência à tipologia dos sistemas de produção no capítulo I e aborda, no capítulo II, as principais funções do planeamento, programação e controlo da produção em contexto MRP, normalmente considerada uma visão mais clássica do tema. Outras duas aproximações com expressividade, a Teoria das Restrições e o JIT/Lean, são abordadas nos capítulos III e IV respetivamente. No capítulo V, o livro finaliza o seu conteúdo com uma breve referência a sistemas de informação empresariais, particularmente vocacionados para contextos de produção. Os autores expressam o seu agradecimento a todos os colegas, alunos e editor, que, com os seus contributos, permitiram chegar ao documento que agora disponibilizamos. Esperamos que lhe seja útil, prezado leitor, que suscite em si a mesma satisfação que o seu longo processo de compilação nos proporcionou, e que possa vir a ser, em próxima revisão, enriquecido com as valiosas críticas, sempre bem-vindas, que haja por bem dedicar-lhe.

Abstract
This paper presents a framework for simulator development for fixed horizon, rolling horizon and real time management models for their modelling and evaluation in ubiquitous production networks under conditions of dynamic environments for economic and environmental sustainability.

Abstract
For manufacturing systems, Industry 4.0 (I4.0) is currently considered a big challenge and is closely related to intelligent manufacturing or production, alongside a more or less wide set of technologies, methodologies, frameworks, tools and techniques. I4.0 encompasses a diversity of approaches to enable the progress of production systems, resulting in shortened production times, production efficiencies, product quality, customization and flexibility of performance. Due to the general awareness about the importance of enabling intelligent manufacturing alongside sustainable production, sustainability is gaining renewed importance. Due to the importance of the theme, there is a need for an updated review of the main enabling approaches of I4.0 for sustainable manufacturing systems. For this purpose, a literature review was conducted considering the research question: Is there increased attention being given to sustainability issues nowadays in Industry 4.0? Through this work, it was possible to verify the main I4.0 and sustainability pillars considered in academia, which for I4.0 are the integration of horizontal and vertical systems, with 94% of the relevant articles mentioning this pillar. The additive manufacturing and 3D printing was refered in 56% of the relevant articles, and for sustainability, the economic pillar was mentioned with 95%, being the main one, with a large difference from other factors.

Abstract
Industry 4.0 represents a turning point in the thinking of the production model since it is based on digitalized production systems with the aim of improving productivity, product quality, and delivery time to the customer. The digitalization and evolution of information technology allowed the emulation of production system virtual models, namely in the concept of Digital Twin (DT), with the ability to simulate different scenarios providing support for better decision making. This concept not only represents a virtual copy of the physical world that obtains information about the state of the value chain but also illustrates a system capable of changing the development of the production activity according to the fulfillment of the intended business goals. In literature, the concept of the Digital Twin is exhaustively treated as a stand-alone factory (one digital factory represents one physical factory) and underestimates the possibility of a DT oriented to a customized product (a project) that requires decentralized production systems. This paper brings to discussion the relevance of product customized applying DT to smart customization, and the inclusion of decentralized production systems supported by Cloud Manufacturing. © 2024 The Author(s). Published by Elsevier B.V.