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Airline scheduling is an extremely complex process. Moreover, disruption in a single flight may damage the entire schedule tremendously. Using an efficient recovery scheduling strategy is vital for a commercial airline. The purpose of this paper is to present an integrated aircraft and crew recovery plans to reduce delay and prevent delay propagation on airline schedule with the minimum cost.

A mixed-integer linear programming model is proposed to formulate an integrated aircraft and crew recovery problem. The main contribution of the model is that recovery model is formulated based on individual flight legs instead of strings. This leads to a more accurate schedule and better solution. Also, some important issues such as crew swapping, reassignment of aircraft to other flights as well as ground and sit time requirements are considered in the model. Benders’ decomposition approach is used to solve the proposed model.

The model performance is also tested by a case including 227 flights, 64 crew, 56 aircraft and 40 different airports from American Airlines data for a 24-h horizon. The solution achieved the minimum cost value in 35 min. The results show that the model has a great performance to recover the entire schedule when disruption happens for random flights and propagation delay is successfully limited.

The authors confirm that this is an original paper and has not been published or under consideration in any other journal.

The purpose of this study is to examine the question of whether the repatriation adjustment process varies with different combinations of duration and purpose of international assignments.

A multiple-case study within one company was conducted based on in-depth interview data.

The authors find that learning-driven international assignments are more beneficial for career growth and receive better organizational support, as assignees are able to maintain regular communication (visibility) with the home unit. On the other hand, those on demand-driven, long-duration international assignments need to have a closer connection (integration) with employees in the host unit and find it challenging to maintain high visibility in the home unit simultaneously.

The authors contribute to existing research by highlighting that demand-driven assignees on longer assignments face greater challenges upon returning home. In addition, expatriates on short-term assignments face drastically fewer challenges than expatriates on longer assignments.

Business graduates’ enterprising capability augments their work readiness, transforming them into professionals capable of driving successful outcomes. At the core lie self-confidence and negotiating competence. However, embedding enterprise education and developing assessments to evidence learning is challenging. This study aims to offer a blueprint for establishing enterprise learning in the classroom and investigating the effectiveness of cultivating negotiating competence and self-confidence.

Modelled on Kolb’s experiential learning cycle, students engage in in-class and real-life negotiations, assessing self-confidence using a scale founded in Bandura’s self-efficacy theory. Open-ended reflections are also submitted. Quantitative data is analysed through multiple linear regression, while quantitative and qualitative data triangulation substantiates enterprise learning in negotiating competence and self-confidence.

Students’ reflections show that low self-confidence poses an initial barrier in negotiations, overcome with successive engagements. Quantitative analysis uncovers response-shift biases, with female and male students overestimating initial self-confidence levels. The gender and difference score type interaction reveals a more pronounced bias among female students starting from a lower baseline than male students, implying a more substantial self-confidence improvement for female students. These findings challenge traditional assumptions about gender differences in negotiations and emphasize the need for nuanced perspectives.

Enterprising capability is pivotal for business professionals. This study highlights the advancement of negotiating competence and self-confidence. It contributes uniquely to the development of enterprise education pedagogy. Focusing on nuanced gender differences challenges prevailing assumptions, providing a perspective to the discourse on negotiating competence and self-confidence in management training.

In repetitive projects, repetition offers more possibilities for activity scheduling at the sub-activity level. However, existing resource-constrained repetitive scheduling problem (RCRSP) models assume that there is only one sequence in performing the sub-activities of each activity, resulting in an inefficient resource allocation. This paper proposes a novel repetitive scheduling model for solving RCRSP with soft logic.

In this paper, a constraint programming model is developed to solve the RCRSP using soft logic, aiming at the possible relationship between parallel execution, orderly execution or partial parallel and partial orderly execution of different sub activities of the same activity in repetitive projects. The proposed model integrated crew assignment strategies and allowed continuous or fragmented execution.

When solving RCRSP, it is necessary to take soft logic into account. If managers only consider the fixed logic between sub-activities, they are likely to develop a delayed schedule. The practicality and effectiveness of the model were verified by a housing project based on eight different scenarios. The results showed that the constraint programming model outperformed its equivalent mathematical model in terms of solving speed and solution quality.

Available studies assume a fixed logic between sub-activities of the same activity in repetitive projects. However, there is no fixed construction sequence between sub-activities for some projects, e.g. hotel renovation projects. Therefore, this paper considers the soft logic relationship between sub-activities and investigates how to make the objective optimal without violating the resource availability constraint.

Construction education rarely addressed the importance of disseminating knowledge on infrastructure equity, thus impeding progress toward creating equitable and sustainable developments. This study aims to investigate the existing sustainability courses under the American Council for Construction Education (ACCE) accredited construction management (CM) programs to examine the integration of infrastructure equity topics and assess improvement in CM students’ knowledge and awareness to address this issue through an intervention.

To achieve these objectives, this research reviewed the sustainability course descriptions of the ACCE-accredited undergraduate and graduate CM curricula. Furthermore, the study implemented a workshop within a CM sustainability course that taught the students about the key concepts of infrastructure equity as well as how to address this issue by leveraging the Envision infrastructure rating system.

The course review results showed that most sustainability courses lack topics such as infrastructure equity and social sustainability. Moreover, the analysis of pre- and postworkshop surveys indicated that guided training could improve the students’ understanding as well as boost their confidence to address and mitigate infrastructure inequity issues.

The findings of the study are valuable for increasing awareness of infrastructure equity and facilitating the future construction workforce with the required expertise to develop equitable infrastructure systems.

Photogrammetry enables scientists and engineers to make accurate and precise measurements from optical images and other patterns of reflected electromagnetic energy. Photogrammetry is taught in surveying, geomatics and similar academic programs. For a long time, it has been observed that there is a lack of diversity and underrepresentation of different groups in the surveying and geomatics workforces for various reasons. Diversity fosters more innovative environments, helps employees be more engaged and boosts productivity rates. Although efforts are being made to solve this problem, most attempts did not significantly improve the diversity issues in this field. To address this problem, we designed a new curriculum for a photogrammetry course, which integrates entrepreneurial mindset (EM), bio-inspired design and Science, Technology, Engineering, Arts and Mathematics (STEAM) into the photogrammetry course for this study.

In this study, the participatory action research method, Photovoice, was used to gather data. Students were asked to respond to photovoice and metacognitive reflection prompts to understand student perceptions about the importance of Unmanned Aerial Vehicles (UAVs) in photogrammetric mapping. Students were required to respond to each prompt with three pictures and a narrative. These reflections were analyzed using thematic analysis.

The analysis of the photovoice and metacognitive reflections resulted in six themes: promoting digital literacy, promoting job readiness and awareness, improving perceived learning outcomes, increasing interest in pursuing careers in surveying/geomatics, encouraging learner engagement and increasing awareness of the role of art in map making.

This is the first study conducted at our Hispanic Serving Institution, which specifically designed a curriculum integrating EM, bio-inspired design and STEAM concepts to address diversity issues in surveying and geomatics engineering disciplines.

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.

This article aims to examine the manifestation of coloniality within social studies curricula and explore strategies for rejecting colonial paradigms through teaching praxis. The author presents a curriculum that unveils the narratives of Linnentown, a local Black community, to examine the impacts of colonial legacies on people's everyday lives.

Using the teaching and learning cycle framework, the author demonstrates the integration of sequenced embodied and multimodal activities. Furthermore, the author utilizes the concept of critical place-based education (CPBE) to demonstrate how critical pedagogies within the context of place can cultivate transformative learning experiences.

By guiding students to critically analyze the sociopolitical conditions of Linnentown residents, CPBE, paired with multimodal activities, helps challenge dominant narratives and empowers students to become agents of change in their local communities.

This curriculum fosters a nuanced understanding of structural oppression, empowers students to develop critical awareness and social agency and guides youth in confronting settler colonialism within and beyond their communities.

The purpose of this paper is to propose a framework of green strategies as a combination of energy-efficiency measures and solutions towards environmental impact reduction for improving environmental sustainability at logistics sites. Such measures are examined by discussing the related impacts, motivations and barriers that could influence the measures' adoption. Starting from the framework, directions for future research in this field are outlined.

The proposed framework was developed starting from a systematic literature review (SLR) approach on 60 papers published from 2008 to 2022 in international peer-reviewed journals or conference proceedings.

The framework identifies six main areas of intervention (“green strategies”) towards green warehousing, namely Building, Utilities, Lighting, Material Handling and Automation, Materials and Operational Practices. For each strategy, specific energy-efficiency measures and solutions towards environmental impact reduction are further pinpointed. In most cases, “green-gold” measures emerge as the most appealing, entailing environmental and economic benefits at the same time. Finally, for each measure the relationship with the measures' primary impacts is discussed.

From an academic viewpoint, the framework fills a major gap in the scientific literature since, for the first time, this study elaborates the concept of green warehousing as a result of energy-efficiency measures and solutions towards environmental impact reduction. A classification of the main areas of intervention (“green strategies”) is proposed by adopting a holistic approach. From a managerial perspective, the paper addresses a compelling need of practitioners – e.g. logistics service providers (LSPs), manufacturers and retailers – for practices and solutions towards greener warehousing processes to increase energy efficiency and decrease the environmental impact of the practitioners' logistics facilities. In this sense, the proposed framework can provide valuable support for logistics managers that are about to approach the challenge of turning the managers' warehouses into greener nodes of the managers' supply chains.

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.