Abstract
Lot-sizing and scheduling in a job shop environment is a fundamental problem that appears in many industrial settings. The problem is very complex, and solutions are often needed fast. Although many solution methods have been proposed, with increasingly better results, their computational times are not suitable for decision-makers who want solutions instantly. Therefore, we propose a novel greedy heuristic to efficiently generate production plans and schedules of good quality. The main innovation of our approach represents the incorporation of a simulation-based technique, which directly generates schedules while simultaneously determining lot sizes. By utilising priority rules, this unique feature enables us to address the complexity of job shop scheduling environments and ensures the feasibility of the resulting schedules. Using a selection of well-known rules from the literature, experiments on a variety of shop configurations and complexities showed that the proposed heuristic is able to obtain solutions with an average gap to Cplex of 4.12%. To further improve the proposed heuristic, a cooperative coevolutionary genetic programming-based hyper-heuristic has been developed. The average gap to Cplex was reduced up to 1.92%. These solutions are generated in a small fraction of a second, regardless of the size of the instance.

Abstract
PurposeTo develop, implement and assess the results of psychoeducation to improve the QoL of parents with CHD newborns.MethodsParticipants were parents of inpatient newborns with the diagnosis of non-syndromic CHD. We conducted a parallel RCT with an allocation ratio of 1:1 (intervention vs. control), considering the newborns, using mixed methods research. The intervention group received psychoeducation (Parental Psychoeducation in CHD [PPeCHD]) and the usual routines, and the control group received just the regular practices. The allocation concealment was assured. PI was involved in enrolling participants, developing and implementing the intervention, data collection and data analysis. We followed the Consolidated Standards of Reporting Trials (CONSORT) guidelines.ResultsParents of eight newborns were allocated to the intervention group (n = 15 parents) and eight to the control group (n = 13 parents). It was performed as an intention-to-treat (ITT) analysis. In M2 (4 weeks), the intervention group presented better QoL levels in the physical, psychological, and environmental domains of World Health Organization Quality of Life instrument (WHOQOL-Bref). In M3 (16 weeks), scores in physical and psychological domains maintained a statistically significant difference between the groups.ConclusionsThe PPeCHD, the psychoeducational intervention we developed, positively impacted parental QoL. These results support the initial hypothesis. This study is a fundamental milestone in this research field, adding new essential information to the literature.

Abstract
This work delves into the crucial role of service quality in the water supply and sanitation sectur. Despite extensive research and implementation of quality management practices in this sector, a universally accepted definition of quality is still lacking, resulting in varikoza service quality assesunent procedures that are difficult to compam. To address this issue, the World Bank launched the Thility of the Future' (UoF) programme, aiming guide water service providers in their efforts to become future-focused utilities that offer reliable, safe, Inclusive, transparent, and resposesive services through best-fit practices. Building upon the Damework provided by the lof programme, this study proposes the Water Utility Service Quallity Index (WUSOI) composite Indicator that reflects the quality of service provided by water supply and sanitation utilities from a customer perspective. Based on Data Envelopment Analysis, the Benelli-of-the-Douht appenach is employed to assign weights for aggregating the indicators representing the diverse performance dimensions. The study operationalines the WUSOI to assess the quality of Purtuguese wholesale water and wastewater companies using data enflected by the national regulator of water and waste services. A Multiple Criteria Decision Analysis technique, the Deck of Cands method, is used to specify an indicator of transparency from the information made available by the regulated utilities. The results show the effectiveness of this tool for evaluating and measuring service quality at the company level. Additionally, the findings highlight areas for Improvement in the utilities' performance. By enabling companies and regulators to identify areas for improvement, the WUSOI can support the delivery of high-quality services to customers.

Abstract
Nowadays, health systems comprise a series of resources structured to provide healthcare services to meet our health needs. However, premature deaths still occur. To quantify and understand personal healthcare conditions affecting such amenable mortality, the Healthcare Access and Quality Index (HAQI) was put forward, evaluating 195 countries and territories since 1990. Nevertheless, the literature acknowledges a series of limitations of this framework, such as the drawbacks of using principal component analysis to aggregate individual indicators, the absence of control for financing and environmental conditions, and the presence of a substantial degree of data uncertainty. Accordingly, we propose a methodological alternative to the computation of the HAQI using a novel fuzzy Data Envelopment Analysis model to handle the aforementioned shortcomings. We also propose its extension towards the quantification of efficiency (E-HAQI) - in the sense of value for money - by incorporating financial aspects as modelling inputs. This way, we contribute with innovative modelling approaches that can also deal with the high degree of data uncertainty. Furthermore, in a second -stage analysis, the impact of key exogenous factors on healthcare access and quality is assessed via non -parametric hypothesis testing. Our results show positive and significant correlations of both the revisited HAQI and E-HAQI with the original HAQI 2016 dataset. They also reveal a better use of resources by European and Oceanian countries and territories than by Sub-Saharan African ones. Concerning contextual determinants, socio-demographic development, human development, and the type of health system were found to be statistically significant drivers of healthcare access and quality efficiency.

Abstract
The complex trajectories of higher education students are deviations from the regular path due to delays in completing a degree, dropping out, taking breaks, or changing programmes. In this study, we investigated degree changing as a cause of complex student trajectories. We characterised cohorts of students who graduated with a complex trajectory and identified the characteristics that influenced the time to graduation. To support this predictive task, we employed machine learning techniques such as neural networks, support vector machines, and random forests. In addition, we used interpretable techniques such as decision trees to derive managerial insights that could prove useful to decision-makers. We validated the proposed methodology taking the University of Porto (Portugal) as case study. The results show that the time to degree (TTD) of students with and without complex trajectories was different. Moreover, the proposed models effectively predicted TTD, outperforming two benchmark models. The random forest model proved to be the best predictor. Finally, this study shows that the factors that best predict TTD are the median TTD and the admission regime of the programme of destination of transfer students, followed by the admission average of the previous programme. By identifying students who take longer to complete their studies, targeted interventions such as counselling and tutoring can be promoted, potentially improving completion rates and educational outcomes without having to use as many resources.

Abstract
Business Process Automation has been gaining increasing importance in the management of companies and organizations since it reduces the time needed to carry out routine tasks, freeing employees for other, more creative and exciting things. It can be applied in the most varied business areas. Organizations from any sector of activity can also adopt it. Given these benefits, the granted success in transforming business processes would be expected. However, automation initiatives still fail. Adopting this technology can raise social, technological, ethical, methodical, and organizational issues. These facts have triggered the necessity for a summary that could extract more information about how to implement Business Process Automation (BPA), attending to the administrative processes, especially when applied in Small and Medium-sized Enterprises (SMEs). This study aims not only to review the available literature on how to implement BPA but also to typify the processes that can be automated, which technologies or tools exist for making that change, and influence factors in the procedure of BPA. We have covered more than 300 research papers published between 2016 and 2023 in reputable scientific data sources like Scopus, Web of Science/Clarivate, and ScienceDirect/Elsevier. The review revealed some paths for BPA, with some common steps. In addition, some common process characteristics fundamental to automation are exposed, as well as factors that are critical to an organization for successful automation. The results indicate that BPA is an established area in Business Process Management related to technologies/tools like Robotic Process Automation (RPA) or Cognitive-Robotic Process Automation (C-RPA), Workflow Management Systems (WfMS), Enterprise Resource Planning (ERP), and Blockchain. As far as we observed, this Systematic Literature Review (SLR) is a unique study that covers all the environmental variables for applying automation in business processes.