Optimizing Storage Location Assignment (SLA) is essential for improving warehouse operations, reducing operational costs, travel distances and picking times. The effectiveness of the optimization process should be evaluated. This study introduces a novel, generalized objective function tailored to optimize SLA through integration with a Genetic Algorithm. The method incorporates key parameters such as item order frequency, storage grouping, and proximity of items frequently ordered together. Using simulation tools, this research models a picker-to-part system in a warehouse environment characterized by complex storage constraints, varying item demands and family-grouping criteria. The study explores four scenarios with distinct parameter weightings to analyze their impact on SLA. Contrary to other research that focuses on frequency-based assignment, this article presents a novel framework for designing SLA using key parameters. The study proves that it is advantageous to deviate from a frequency-based assignment, as considering other key parameters to determine the layout can lead to more favorable operations. The findings reveal that adjusting the parameter weightings enables effective SLA customization based on warehouse operational characteristics. Scenario-based analyses demonstrated significant reductions in travel distances during order picking tasks, particularly in scenarios prioritizing ordered-together proximity and group storage. Visual layouts and picking route evaluations highlighted the benefits of balancing frequency-based arrangements with grouping strategies. The study validates the utility of a tailored generalized objective function for SLA optimization. Scenario-based evaluations underscore the importance of fine-tuning SLA strategies to align with specific operational demands, paving the way for more efficient order picking and overall warehouse management.

The study explores the relationship between authentic leadership, psychological capital, and work engagement among educators in the Makhado Municipality. The primary aim was to assess how authentic leadership influences educators’ psychological capital and examine how psychological capital impacts work engagement. A quantitative research design was employed, utilizing a survey-based approach to collect data from a sample of educators across 15 primary schools within the Makhado Municipality. Structural Equation Modeling was used to analyze the data and test the relationships between authentic leadership, psychological capital, and work engagement. Results indicate that authentic leadership has a significant positive influence on the psychological capital of educators. In turn, psychological Capital was found to have a strong positive impact on work engagement, suggesting that educators who perceive their leaders as authentic are more likely to experience higher levels of psychological well-being and engagement in their work. This study contributes to the literature on leadership and educator well-being by demonstrating the value of authentic leadership in promoting a supportive work environment that enhances educators’ psychological capital and engagement. The educational management and policy implications emphasize the need for leadership development programs that foster authentic leadership behaviors to improve educator performance and overall school effectiveness.

Urban planning is critical to managing rapid urban growth, particularly in African regions experiencing high urbanization rates. This study focuses on Bol, Lake Chad Province, a city facing significant challenges due to inadequate planning frameworks compounded by recurrent humanitarian and climate crises. It fills an empirical gap by analyzing how local planning mechanisms respond to these socio-environmental complexities, with a focus on the interplay between institutional structures, legislative frameworks, and resource allocation. The study assesses urban planning practices in Bol to identify challenges and opportunities, with the aim of improving institutional effectiveness, aligning policies with realities, and integrating climate resilience strategies. Using a qualitative methodology, it combines field surveys, stakeholder interviews, and document analysis, using SWOT (Strengths, Weaknesses, Opportunities, Threats) and PESTEL (Political, Economic, Sociocultural, Technological, Environmental, Legal) frameworks for data analysis. The findings reveal that ineffective institutions, poor inter-sectoral coordination, outdated legislative frameworks and resource constraints hamper sustainable urban development in Bol. To address these issues, the study proposes to strengthen local institutional capacities, foster stakeholder collaboration, and modernize urban planning policies through participatory approaches. The study highlights the need to integrate resilience strategies into urban settings to mitigate climate change impacts and improve governance. These measures not only address immediate challenges, but also advance urban planning theory and provide a basis for future research on adaptation strategies in crisis-prone regions. This study offers practical insights for policy makers and contributes to developing more sustainable and resilient urban planning systems in similar contexts.

Over the past 50 years, urban planning documents have been drawn up in sub-Saharan African cities without any convincing results. The study of secondary towns in Chad shows that these planning documents have been hampered by natural and man-made factors. The aim of this study is to determine the factors hindering the implementation of planning documents in the town of Pala in Chad. To carry out the study, a methodological approach (using quantitative and qualitative data) based on a questionnaire and interview survey was deployed for data collection. With a sample of 300 households surveyed, the main conclusions of the study show that all the factors identified, such as water erosion with a rate of 17.7 T/Ha/year, expose the town to various risks. Demographics, on the other hand, represent a lesser and therefore acceptable challenge. As far as exogenous factors are concerned, the level of education of the head of household is a determining factor in the implementation and acceptance of urban planning documents in Pala. Confirmatory factor analysis and the Chi² test revealed that consideration of stakeholders’ needs and their inclusion in the process of drawing up these documents are factors that significantly influence their implementation. In contrast, age, gender and other variables did not reveal any significant anomalies in our analyses. Consequently, future efforts to implement Pala’s planning documents must be based on community participation and awareness of the acceptance of these documents, which are necessary in a process of decentralization and urban planning.

Rapid population growth and inadequate adherence to scientific and managerial principles in urban planning have intensified numerous challenges, pushing major Iranian cities toward instability. Tehran, as the capital and one of the most urbanized regions in the country, faces significant sustainability threats that require immediate attention. These challenges are not unique to Tehran but represent a broader issue faced by rapidly urbanizing cities worldwide, particularly in developing countries. Addressing such challenges is critical to fostering sustainable development on a global scale. While urban sustainability has been extensively studied, limited research has focused on the indicators of urban instability and their tangible impacts on sustainable urban planning. This study aims to bridge this gap by identifying and analyzing key factors contributing to urban instability across economic, environmental, and social dimensions, with Tehran serving as a representative case. The findings reveal that economic instability is driven by uncertainty in economic policies, fluctuating housing prices, non-standard housing conditions, income disparity, unemployment, and cost of living pressures. Environmental instability is exacerbated by climate change, urban heat islands, floods, transportation mismanagement, energy insecurity, pollution, and insufficient green infrastructure. Social instability arises from limited social interaction, unequal access to services, weak community participation, social harms, and diminished urban safety and welfare. By framing these local challenges within a global context, the study underscores the interconnectedness of these dimensions and highlights the necessity for integrated, evidence-based approaches that combine local insights with global best practices. The findings aim to contribute to the broader discourse on sustainable urban development by offering actionable insights and strategies that can be adapted and implemented in other rapidly urbanizing cities. This research serves as a guide for policymakers, urban planners, and stakeholders worldwide, emphasizing the importance of holistic and resilient urban strategies to address the multifaceted challenges of sustainability and instability.

Artificial intelligence (AI) has rapidly evolved, transforming industries and addressing societal challenges across sectors such as healthcare and education. This study provides a state-of-the-art overview of AI research up to 2023 through a bibliometric analysis of the 50 most influential papers, identified using Scopus citation metrics. The selected works, averaging 74 citations each, encompass original research, reviews, and editorials, demonstrating a diversity of impactful contributions. Over 300 contributing authors and significant international collaboration highlight AI’s global and multidisciplinary nature. Our analysis reveals that research is concentrated in core journals, as described by Bradford’s Law, with leading contributions from institutions in the United States, China, Canada, the United Kingdom, and Australia. Trends in authorship underscore the growing role of generative AI systems in advancing knowledge dissemination. The findings illustrate AI’s transformative potential in practical applications, such as enabling early disease detection and precision medicine in healthcare and fostering adaptive learning systems and accessibility in education. By examining the dynamics of collaboration, geographic productivity, and institutional influence, this study sheds light on the innovation drivers shaping the AI field. The results emphasize the need for responsible AI development to maximize societal benefits and mitigate risks. This research provides an evidence-based understanding of AI’s progress and sets the stage for future advancements. It aims to inform stakeholders and contribute to the ongoing scientific discourse, offering insights into AI’s impact at a time of unprecedented global interest and investment.