2024
Autores
Vanhoucke, M; Coelho, J;
Publicação
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
Abstract
This paper presents a matheuristic solution algorithm to solve the well-known resource-constrained project scheduling problem (RCPSP). The problem makes use of a restricted neighbourhood method using an activity selection and a search space restriction module and implements them as two alternative search algorithms. The first algorithm makes use of the best-performing components of the branch-and-bound procedures from the literature, and embeds them into a greedy neighbourhood search. The second matheuristic implements the exact branch-and-bound procedures into a known and well-performing meta-heuristic search algorithm. Computational experiments have been carried out on seven different datasets consisting of 10,000+ project instances. Experiments reveal that the choice of exact algorithm is key in finding high-quality solutions, and illustrate that the trade-off between selecting an activity set size and search space restriction depends on the specific implementation. The computational tests demonstrate that the matheuristic discovered 24 new best known solutions that could not be found by either a meta-heuristic or an exact method individually. Moreover, a new benchmark dataset has been proposed that can be used to develop new matheuristic search procedures to solve the problem consisting of 461 instances from the literature.
2024
Autores
Servranckx, T; Coelho, J; Vanhoucke, M;
Publicação
ANNALS OF OPERATIONS RESEARCH
Abstract
This article summarises the research studies published in the special issue on Project Management and Scheduling devoted to the 18th International Conference on Project Management and Scheduling (PMS). The special issue contains state-of-the art research in the field of (non-)robust project and machine scheduling and the contribution of each individual study to the academic literature are discussed. We notice that there is a growing interest in the research community to investigate robust scheduling approaches and optimisation problems observed in real-life business settings. This allows us to derive some interesting future research directions for the project and machine scheduling community.
2024
Autores
Silveira, RA; Mamede, HS;
Publicação
SUSTAINABILITY
Abstract
The research objective of this work is to develop and evaluate an enterprise architecture for rural accommodation in the Iberian Peninsula that responds to the demand of the remote labor market. Through an extensive literature review and the application of ArchiMate modeling, this study focuses on providing an enterprise architecture that promotes business resilience and environmental sustainability and boosts the local economy. The proposed enterprise architecture is remotely evaluated by experts, highlighting potential benefits, challenges, and areas for improvement. The results show that the proposed enterprise architecture has the potential to improve the long-term success of rural lodging businesses, enhance the customer experience, promote sustainability, and contribute to economic growth in rural areas through value exchange among stakeholders. The ArchiMate model provides a holistic perspective on stakeholder interactions and interoperability across all functional business areas: Customer Service, Product Management, Omnichannel Commerce, Human Resources, Business Strategy, Marketing, and Sustainability Management. The idea is to empower rural lodging businesses to create a better customer experience, achieve energy and environmental efficiency, contribute to local development, respond quickly to regulatory changes and compliance, and develop new revenue streams. The main goal is to improve offers, mitigate seasonal effects, and reverse the continuous cycle of decline in areas with low population density. Therefore, this ArchiMate modeling can be the initial basis for the digitization or expansion of the rural lodging industry in other geographies.
2024
Autores
Mamede, S; Santos, A;
Publicação
Creating Learning Organizations Through Digital Transformation
Abstract
Organizations find themselves at a pivotal crossroads in an era propelled by the sweeping tide of digital transformation, where the wake of the COVID-19 pandemic has reshaped the global landscape. Within these novel contexts, the imperative to cultivate Learning Organizations (LOs) has emerged as a beacon of adaptability and progress. Creating Learning Organizations Through Digital Transformation weaves the fabric of LOs within the digital tapestry, where minds perpetually expand, and learning begets learning. This journey hinges on the synergy of knowledge and digital prowess, as LOs harness data and digital content with finesse. From immersive learning to artificial intelligence, these technological frontiers reshape learning, spurring change. Unveiling the core concepts, implementations, and global impacts of LOs, this book is a compass for academics, researchers, and practitioners. It deciphers people capacities, digital contents, learning technologies, and evaluation, nurturing the symbiotic relationship between learning and transformation. Creating Learning Organizations Through Digital Transformation is the scholarly guidepost in a swiftly evolving landscape. It beckons to those attuned to academia and those shaping real-world organizations, resonating with the pursuit of knowledge in an era of unceasing change. © 2024 by IGI Global. All rights reserved.
2024
Autores
Arnaud, J; Mamede, HS; Branco, F;
Publicação
INFORMATION SYSTEMS AND TECHNOLOGIES, VOL 3, WORLDCIST 2023
Abstract
We cannot neglect digital literacy because it is undeniable how much technology is part of our lives. Ignoring it and the tools and services it provides us, which greatly facilitate the human experience, is simply a mistake. Recognising the importance of digital literacy, primarily due to the digital transformation in Portugal, it will be necessary to have technological skills to overcome some limitations. Information and Communication Technologies are seen in this environment as a factor that can contribute, on a large scale, to the inclusion of individuals with a digital literacy deficit, both in the Portuguese Local Public Administration and in society in general. The growth of digital transformation causes almost all jobs to need digital skills and participation in society. It takes digitally intelligent employees who know not only to use but also innovate and lead to new technologies because digital transformation may not be successful without that capacity. Thus, it is pertinent to develop, propose and validate an explanatory model that improves the relationship between digital transformation in Portuguese Local Public Administration and the digital literacy of its employees.
2024
Autores
Trovão, H; Mamede, HS; Trigo, P; Santos, V;
Publicação
Lecture Notes in Networks and Systems
Abstract
Human resources play a crucial role in the success of small- and medium-sized enterprises (SMEs), and in today’s competitive recruitment landscape, leveraging technology can be instrumental in enhancing these processes. Organizations and HR departments increasingly adopt artificial intelligence solutions to streamline recruitment and selection procedures. By doing so, SMEs can improve operational efficiency while enabling human resource (HR) specialists to focus on crucial tasks, enhancing candidate experience throughout the recruitment process. However, adopting artificial intelligence (AI) in recruitment remains limited among SMEs. We can attribute this to various factors, including a need for more capacity among SME managers to evaluate and leverage AI’s potential and concerns related to costs and risks associated with its implementation. Given that SMEs constitute 90% of businesses and contribute over 50% of global employment, it is crucial to address this issue and research ways to enhance recruitment processes specifically tailored for SMEs. Our research aims to explore the benefits, challenges, and necessary organizational resources for SMEs to adopt AI effectively in recruitment processes. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
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