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The proposed model aims to consider the flying hours as a criterion to initiate maintenance operation. Based on this condition, aircraft must be checked before flying hours threshold is met. After receiving maintenance service, the model ignores previous flying hours and the aircraft can keep on flying until the threshold value is reached again. Moreover, the model considers aircraft age and efficiency to assign them to flights.

The aircraft maintenance routing problem (AMRP), as one of the most important problems in the aviation industry, determines the optimal route for each aircraft along with meeting maintenance requirements. This paper presents a bi-objective mixed-integer programming model for AMRP in which several criteria such as aircraft efficiency and ferrying flights are considered.

As the solution approaches, epsilon-constraint method and a non-dominated sorting genetic algorithm (NSGA-II), including a new initializing algorithm, are used. To verify the efficiency of NSGA-II, 31 test problems in different scales are solved using NSGA-II and GAMS. The results show that the optimality gap in NSGA-II is less than 0.06%. Finally, the model was solved based on real data of American Eagle Airlines extracted from Kaggle datasets.

The authors confirm that it is an original paper, has not been published elsewhere and is not currently under consideration of any other journal.

In regarding to operational efficiency and safety improvements, multiple tower crane service scheduling problem is one of the main problems related to tower crane operation but receives limited attention. The current work presents an optimization model for scheduling multiple tower cranes' service with overlapping areas while achieving collision-free between cranes.

The cooperative coevolutionary genetic algorithm (CCGA) was proposed to solve this model. Considering the possible types of cross-tasks, through effectively allocating overlapping area tasks to each crane and then prioritizing the assigned tasks for each crane, the makespan of tower cranes was minimized and the crane collision avoidance was achieved by only allowing one crane entering the overlapping area at one time. A case study of the mega project Daxing International Airport has been investigated to evaluate the performance of the proposed algorithm.

The computational results showed that the CCGA algorithm outperforms two compared algorithms in terms of the optimal makespan and the CPU time. Also, the convergence of CCGA was discussed and compared, which was better than that of traditional genetic algorithm (TGA) for small-sized set (50 tasks) and was almost the same as TGA for large-sized sets.

This paper can provide new perspectives on multiple tower crane service sequencing problem. The proposed model and algorithm can be applied directly to enhance the operational efficiency of tower cranes on construction site.

Lifelong learning has become one of the most interesting areas of research. Hence, the current study was aimed at developing and validating a tool that helps to study how well people working in higher education institutions are engaged in lifelong learning.

A review of theories in the literature and experts' consultation were used to develop a pool of items and validate the self-assessment instrument for measuring lifelong learning. The study employed factor analytic methodologies such as principal component analysis, varimax rotation and exploratory factor analyses.

The study yielded a reliable and valid lifelong learning measurement scale made up of 18 items and four underlying factors that are theoretically supported.

The significant information is that, the current study aimed at developing a tool that could help to measure the engagement in lifelong learning of higher education institutions workers. The study found this tool to be important because lifelong learning is considered essential for personal and professional growth, and having a sound way to measure it can help individuals and organizations identify areas for improvement.

Precast wall lifting during prefabricated building construction faces multiple non-lean problems, such as inaccurate lifting-time estimation, unreasonable resource allocation and improper process design. This study aims to identify the pathways for improving lifting performance to advance lean construction of prefabricated buildings.

This study developed a methodological framework that integrates the discrete event simulation method, the elimination, combination, rearrangement and simplification (ECRS) technique and intelligent optimization tool. Two schemes of precast wall lifting, namely, the enterprise's business as usual (BAU) and enterprise-leading (EL) schemes, were set to benchmark lifting performance. Furthermore, a best-practice (BP) scheme was modeled from the perspective of lifting activity ECRS and resource allocation for performance optimization.

A real project was selected to test the effect of the methodological framework. The results showed that compared with the EL scheme, the BP scheme reduced the total lifting time (TLT) by 6.3% and mitigated the TLT uncertainty (the gap between the maximum and minimum time values) by 20.6%. Under the BP scheme, increasing the resource inputs produces an insignificant effect in reducing TLT, i.e. increasing the number of component operators in the caulking subprocess from one to two only shortened the TLT by 3.6%, and no further time reduction was achieved as more component operators were added.

To solve non-lean problems associated with prefabricated building construction, this study provides a methodological framework that can separate a typical precast wall lifting process into fine-level activities. Besides, it also identifies the pathways (including the learning effect mitigation, labor and machinery resource adjustment and activities’ improvement) to reducing TLT and its uncertainty.

Civil engineering projects around the world have been underperforming for a long time. While the complexity of these projects will continue to increase, there is an urgent need to perform better. Although the integrated design process is critical for project success, the literature lacks studies describing the link to project performance. Therefore, this study aims to investigate the dominant variables that affect the integrated design process and consequently project performance.

A multiple case study was conducted to determine the dominant variables that affect the integrated design process and project performance. The research included four projects. Semi-structured interviews were the main source of data.

The cases indicated that the extent to which an integrated approach is achieved in the design process is essential for project performance. This applies to the integration of stakeholders’ interests as well as the integration of disciplines. Above all, it was concluded that the project team participants’ competencies for integration are a dominant factor for project performance, as the integrated design process has changed from a technical challenge to an integrative one.

This study provides insights into the dominant variable of the integrated design process that affects project performance, which is underexposed in the literature. The study results reveal the importance of competencies related to integration and adoption of the design problem context, which are not yet included in civil engineering design methods. In this respect, empathy is introduced as a new and critical competence for the civil engineering industry, which needs further research.

This study aims to address this unexplored influence of international assignment types on the development, transfer and utilization of career capital by assigned repatriates from host to home country. In response to existing literature gap, it aligns with the need for qualitative case studies that delve into threats to the self-reinforcement of repatriates' career capital.

By mean of a qualitative case study, this paper deepens understanding of linkages and processes in career capital development and clarify the interplay between individual interpretations of career actions and the organizational context in which they unfold. Nineteen qualitative interviews with assigned repatriates explored the impact of exposure to new career contexts.

This study provides valuable insights into the complex dynamics of career capital development and transfer during international assignments. It elucidates the impact of career context on assigned repatriates' career capital, emphasizing challenges in career capital generation, dispersion and absorption within multinational enterprises. It contributes to understanding the complexities of (new) managerial capacity development by revealing varied effects that international assignments can exert on individuals' immediate competencies and career capital.

If the assigned expatriate/repatriate’s understanding of the firm’s assignment motive, and their own motive (understanding/reason) for the assignment corresponds then expectations of outcomes can be better managed. Organizations otherwise run the risk of perpetuating inequities in the career development opportunities of employees.

Studies on career capital emphasize its qualities or examine different globally mobile employee types. Yet there's a gap in understanding how the type of assignment impacts career capital development, transfer and utilization. This research fills this void by investigating the international transfer of career capital from host to home country specifically for assigned repatriates.

Companies target globally mobile workers and face the war for talent, while individuals are more reluctant to engage in global mobility. This scenario led us to propose a model to understand the individuals' decision process to engage in global mobility.

Building on the self-determination theory, the theory of planned behavior and the literature on decisions for global mobility, the authors propose mechanisms through which psychological variables and assignments' factual and perceived contextual aspects (directly or indirectly) explain the decision to engage or not in global mobility.

This study offers a conceptual model with the authors' novel propositions to explain individuals' decision to engage in global mobility.

The model provides a more comprehensive explanation of the individuals' decision-making process to engage in global mobility than previous models and potentially yields more effective organizational practices to attract both well-established and emerging phenomena of globally mobile workers.

This article describes an effort to ease the tension between boundary spanning roles for interns participating in a yearlong Professional Development School (PDS) program. In order to do this, the structure of a Social Studies Methods course was revised to mimic a professional learning community (PLC) and assignments were not evaluated for grades.

A conceptual paper that relies on self-reflection as well as student reaction, work samples and survey data.

The findings demonstrate both practices contribute to a collegial and less stressful environment for interns, while not affecting the quality of work submitted.

This paper highlights two of the nine NAPDS essentials, Professional Learning and Leading (3) and Boundary Spanning (8), and describes the ways both are incorporated and addressed in a PDS situated methods course. Describing course revisions, including the implementation of an ungrading practice, provides examples for potential replication.

This paper aims to establish an efficient maintenance management system tailored for healthcare facilities, recognizing the crucial role of medical equipment in providing timely and precise patient care.

The system is designed to function both as an information portal and a decision-support system. A knowledge-based approach is adopted centered on Semantic Web Technologies (SWTs), leveraging a customized ontology model for healthcare facilities’ knowledge capitalization. Semantic Web Rule Language (SWRL) is integrated to address decision-support aspects, including equipment criticality assessment, maintenance strategies selection and contracting policies assignment. Additionally, Semantic Query-enhanced Web Rule Language (SQWRL) is incorporated to streamline the retrieval of decision-support outcomes and other useful information from the system’s knowledge base. A real-life case study conducted at the University Hospital Center of Oran (Algeria) illustrates the applicability and effectiveness of the proposed approach.

Case study results reveal that 40% of processed equipment is highly critical, 40% is of medium criticality, and 20% is of negligible criticality. The system demonstrates significant efficacy in determining optimal maintenance strategies and contracting policies for the equipment, leveraging combined knowledge and data-driven inference. Overall, SWTs showcases substantial potential in addressing maintenance management challenges within healthcare facilities.

An innovative model for healthcare equipment maintenance management is introduced, incorporating ontology, SWRL and SQWRL, and providing efficient data integration, coordinated workflows and data-driven context-aware decisions, while maintaining optimal flexibility and cross-departmental interoperability, which gives it substantial potential for further development.

This paper aims to propose a robust method for non-rigid point set registration, using the Gaussian mixture model and accommodating non-rigid transformations. The posterior probabilities of the mixture model are determined through the proposed integrated feature divergence.

The method involves an alternating two-step framework, comprising correspondence estimation and subsequent transformation updating. For correspondence estimation, integrated feature divergences including both global and local features, are coupled with deterministic annealing to address the non-convexity problem of registration. For transformation updating, the expectation-maximization iteration scheme is introduced to iteratively refine correspondence and transformation estimation until convergence.

The experiments confirm that the proposed registration approach exhibits remarkable robustness on deformation, noise, outliers and occlusion for both 2D and 3D point clouds. Furthermore, the proposed method outperforms existing analogous algorithms in terms of time complexity. Application of stabilizing and securing intermodal containers loaded on ships is performed. The results demonstrate that the proposed registration framework exhibits excellent adaptability for real-scan point clouds, and achieves comparatively superior alignments in a shorter time.

The integrated feature divergence, involving both global and local information of points, is proven to be an effective indicator for measuring the reliability of point correspondences. This inclusion prevents premature convergence, resulting in more robust registration results for our proposed method. Simultaneously, the total operating time is reduced due to a lower number of iterations.