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 application of optimization algorithms is crucial for analyzing oil and gas company portfolio and supporting decision-making. The paper investigates the process of optimizing a portfolio of oil and gas projects under economic uncertainty. The literature review explores the advantages of applying various optimizers to models that consider the mean and semi-standard deviations of stochastic multi-year cash flows and revenues. The methods and results of three different optimization algorithms are discussed: ranking and cutting algorithms, linear (Simplex) and evolutionary (genetic) algorithms. Functions of several key performance indicators were used to test these algorithms. The results confirmed that multi-objective optimization algorithms that examine various key performance indicators are used for efficient optimization in oil and gas companies. This paper proposes a multi-criteria optimization model for investment portfolios of oil and gas projects. The model considers the specific features of these projects and is based on the Markowitz portfolio theory and methodological recommendations for project assessment. An example of its practical application to oil and gas projects is also provided.

The sustainable development of Madeira Island necessitates the implementation of more precise and targeted planning strategies to address its regional challenges. Given the urgency of this issue within the context of sustainability, planning approaches must be grounded in and reinforced by a comprehensive array of thematic studies to fully grasp the complexities involved. This research leverages Geographic Information Systems (GIS) to analyze land use and occupancy patterns and their evolution within the municipality of Machico on Madeira Island. The study provides a nuanced perspective on the urban structure’s stagnation in the region, while concurrently highlighting the dynamic shifts in agricultural practices. Furthermore, it elucidates the transformation of predominant native vegetation within the municipality from 1990 to 2018. Notably, the research underscores the alarming decline in native vegetation due to anthropogenic activities, emphasizing the need for more rigorous monitoring by regional authorities to safeguard and preserve these valuable landscapes, habitats, and ecosystems.

The internationalization of higher education began to take shape during the period of the Republic of China. This trend manifested in various forms and encompassed a rich array of activities, including the construction of teaching staffs, the exchange of international students, and the presence of overseas scholars giving lectures in China. Between 1899 and 1945, Japanese institutions sent nearly 200 academic overseas students to China. With the establishment and improvement of the internal system of universities in the Republic of China, these students were able to study and interact with Chinese scholars. The forms of communication were diverse, the content was rich, and the channels were smooth, making the process lively and interesting with distinct characteristics of the era. Consequently, this group became both participants and witnesses in the internationalization process of universities in the Republic of China. However, the full-scale Anti-Japanese War disrupted the internationalization of universities, causing it to deviate from its normal trajectory. Some Japanese academic overseas students who had previously studied in China became instruments of Japanese imperialism’s cultural invasion and educational colonization. These students played a significant role in promoting the “alternative internationalization” of universities in the Republic of China. In short, examining the involvement of Japanese academic overseas students providing us a unique insight into the general situation and processes of internationalization at universities in the Republic of China during different historical periods.