Abstract
A realidade com a qual lidamos atualmente é absolutamente desafiadora no que diz respeito aos nossos paradigmas de resolução de problemas mais conservadores. Os avanços tecnológicos, as transformações sociais, bem como os perfis dos atuais líderes (nas empresas ou nas instituições públicas) destas primeiras décadas do milénio, implicam que os gestores e futuros executivos estejam adequadamente preparados para responder com sucesso a esta Nova Era em que a Revolução Industrial 4.0 (I4.0), se está desenvolvendo. Conscientes desses enormes desafios, foi desenvolvido um projeto internacional durante cerca de três anos com diferentes propostas educativas e que agora se apresentam, avaliam e exigem a nossa reflexão. Procurando responder às múltiplas solicitações que os empregadores reclamam repetidamente sobre o gap que existe entre as competências desenvolvidas na Academia e as que são necessárias no Contexto Industrial, o projeto Universities of the future - UoF, procurou diminuir o fosso entre estas duas realidades através de uma oferta formativa diferente, (co)construída entre equipas representantes de diferentes contextos para um melhor perfil de competências dos “executivos/as 4.0”.

Abstract
Due to the competitiveness in the job shop nature of the metalworking industry, project management plays an important role in improving performance, efficiently and effectively managing its performance. Many of the generic problems observed in project management in metalworking industries were in the domain of document management, communication, multiple projects simultaneously, organizational structure, and poorly time estimation of project activities. The aim of this study was to improve the planning and time control in the project management of a metalworking industry in order to reduce the delivery delays. Using the existing data, an analysis of the project management process was carried out with the view to optimize the production system. In order to meet the established objectives, some of the project management tools were used, such as the Ishikawa diagram, PERT (three points estimating times), Monte Carlo simulation, as well as the involvement of people in the estimation and sequencing of activities, and holding weekly meetings to ensure the alignment of professionals. After the implementation of the actions proposed for the production process, there were gains of 50% and 38% in the average of deviations of times for two different projects of the case study and the Monte Carlo gave the best approximation.

Abstract
The innovation and digitalization of the industry is happening triggered by the Industry 4.0 and Industrial Internet-of-Things (IIoT) paradigm. Enterprises are following the trend of digital transformation and are fostering projects that enable a higher comprehension of I4.0 solutions to answer their needs. The IIoT platforms have been a central component for industrial systems architectures to enable interoperability and data flow within industrial settings. However, the digitalization process has all sorts of shortcomings associated to them, and in the SME's this transformation has been slow to none. In this work we showcase a proof of concept of an IIoT platform that intends to simplify the digitalization process in SME's, based on the Portuguese footwear industry cluster.

Abstract
Kidney exchange programs aim at matching end-stage renal disease patients who have a willing but incompatible kidney donor with another donor. The programs comprise a pool of such incompatible patient-donor pairs and, whenever a donor from one pair is compatible with the patient of another pair, and vice versa, the pairs may be matched and exchange kidneys. This is typically a two-step process in which, first, a set of pairs is matched based on preliminary compatibility tests and, second, the matched pairs are notified and more accurate compatibility tests are performed to verify that actual transplantation can take place. These additional tests may reveal incompatibilities not previously detected. When that happens, the planned exchange will not proceed. Furthermore, pairs may drop out before the transplant, and thus the planned exchange is canceled. In this paper, we study the case in which a new set of pairs may be matched if incompatibilities are discovered or a pair withdraws from the program. The new set should be as close as possible to the initial set in order to minimize the material and emotional costs of the changes. Various recourse policies that determine the admissible second-stage actions are investigated. For each recourse policy, we propose a novel adjustable robust integer programming model. Wealso propose solution approaches to solve this model exactly. The approaches are validated through thorough computational experiments. Summary of Contribution: In the paper, we present an original work related to the modeling and optimization approaches for Kidney Exchange Programs (KEPs). Currently, KEPs represent an alternative way for patients suffering from renal failure to find a compatible (living) donor. The problem of determining an assignment of patients to (compatible) donors that maximizes the number of transplants in a KEP can be seen as a vertex-disjoint cycle packing problem. Thus, KEPs have been extensively studied in the literature of integer programming. In practice, the assignment determined to a KEP might not be implemented due to withdraws from the program (e.g., a more accurate compatible test shows a new incompatibility or a patient health condition unable him/her to participate on the KEP). In our paper, we model the problem of determining a robust solution to the KEP, i.e., a solution that minimizes the material and emotional costs of changing an assignment. In this way, we propose and design solution approaches for three recourse policies that anticipate withdraws. Through computational experiments we compare the three recourse policies and validate the practical interest of robust solutions.

Abstract
Nowadays there are several countries running independent kidney exchange programmes (KEPs). These programmes allow a patient with kidney failure, having a willing healthy but incompatible donor, to receive a transplant from a similar pair where the donor is compatible with him. Since in general larger patient-donor pools allow for more patients to be matched, this prompts independent programmes (agents) to merge their pools and collaborate in order to increase the overall number of transplants. Such collaboration does however raise a problem: how to assign transplants to agents so that there is a balance between the contribution each agent brings to the merged pool and the benefit it gets from the collaboration. In this paper we propose a new Integer Programming model for multi-agent kidney exchange programmes (mKEPs). It considers the possible existence of multiple optimal solutions in each matching period of a KEP and, in consecutive matching periods, selects the optimal solution among the set of alternative ones in such a way that in the long-term the benefit each agent gets from participating in the mKEP is balanced accordingly to a given criterion. This is done by use of a memory mechanism. Extensive computational tests show the benefit of mKEPs, when compared to independent KEPs, in terms of potential increase in the number of transplants. Furthermore, they show that, under different policies, the number of additional transplants each agent receives can vary significantly. More importantly, results show that the proposed methodology consistently obtains more stable results than methodologies that do not use memory.

Abstract
The complex multi-criteria optimisation problems arising in Kidney Exchange Programmes have received considerable attention both in practice and in the scientific literature. Whereas theoretical advancements are well reviewed and synthesised, this is not the case for practice. We present a synthesis of models and methods applied in present European Kidney Exchange Programmes, which is based on detailed descriptions we created for this purpose. Most descriptions address national programmes, yet we also present findings on emerging cross-national programmes. The synthesis provides a systematic and detailed description of the models and methods the programmes use, revealing important commonalities as well as considerable variation among them. Rather than distilling a single best practice from these results, we find that the variation in models and methods arises because of variation in country characteristics, policies, and ethics. The synthesised state of the art may benefit future national and cross-national initiatives and direct future theoretical contributions within and across the boundaries of the Operations Research discipline. (c) 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)