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.

This study investigates how financial cognitive abilities influence individual investors’ intentions to engage in the stock market, particularly considering the mediating role of financial capability. It seeks to address the gaps in understanding the factors that drive investors’ participation in emerging markets like Pakistan, highlighting the importance of financial knowledge, financial planning, and financial satisfaction and financial capability. Data were collected from 377 individual investors through a self-administered questionnaire using a cross-sectional design and non-probability convenience sampling approach. Results reveal that financial knowledge affects investors’ intentions both directly and indirectly, with financial capability serving as a partial mediator. Financial planning influences intentions indirectly through complete mediation, while financial satisfaction affects intentions in both direct and indirect ways, with partial mediation. The study provides valuable insights for the researchers, individual investors, governmental officials, policymakers, and stock market regulators in context of emerging economies like Pakistan, highlighting key determinants of stock market participation.

The target date for achieving the 2030 UN Agenda [Sustainable Development Goals (SDGs)] is fast approaching. The construction sector is critical to achieving many SDGs, including Goal 5. Studies regarding achieving Goal 5 (Gender Equality) in the construction industry, especially women’s consultancy participation in developing countries, are scarce and complexly interrelated. Societal problems and divergence may have contributed to this. Therefore, this study explores issues hindering gender equality and suggests measures to promote more women construction consultants through policy to improve achieving Goal 5 in Nigeria. The research employed face-to-face data collection via a qualitative mechanism to achieve this. The study covered Abuja and Lagos. It accomplished saturation at the 20th participant. The research utilised a thematic method to analyse the collected data from knowledgeable participants. The perceived hindrances facing Nigerian construction consultants’ gender equality were clustered into culture/religion-related, profession-related, and government-related encumbrances. Achieving Goal 5 will be a mirage if these issues are not addressed. Thus, the study recommended measures to motivate women to study construction-related programmes and employment opportunities, including consultancy services slots through programmes and policy mechanisms to achieve Goal 5. As part of the implications, the study suggests that Nigerian construction consultants and other stakeholders need to make feasible improvements to achieve gender equality (Goal 5).

A Detailed geophysical investigation was conducted on Knossos territory of Crete Island. Main scope was the detection of underground archaeological settlements. Geophysical prospecting applied by an experienced geophysical team. According to area dimensions in relation to geological and structural conditions, the team designed specific geophysical techniques, by adopted non-catastrophic methods. Three different types of geophysical techniques performed gradually. Geophysical investigation consisted of the application of geoelectric mapping and geomagnetic prospecting. Electric mapping focusses on recording soil resistance distribution. Geomagnetic survey was performed by using two different types of magnetometers. Firstly, recorded distribution of geomagnetic intensity and secondly alteration of vertical gradient. Measured stations laid along the south-north axis with intervals equal to one meter. Both magnetometers were adjusted on a quiet magnetic station. Values were stored in files readable by geophysical interpretation software in XYZ format. Oasis Montaj was adopted for interpretation of measured physical properties distribution. Interpretation results were illustrated as color scale maps. Further processing applied on magnetic measurements. Results are confirmed by overlaying results from three different techniques. Geoelectric mapping contributed to detection of a few archaeological targets. Most of them were recorded by geomagnetic technique. Total intensity aimed to report the existence of magnetized bodies. Vertical gradient detected subsurface targets with clearly geometrical characteristics.

The golden visa is a regulation designed to facilitate foreign nationals through a residence permit scheme with an emphasis on investment and citizenship. This research aims to look at the development of the golden visa as an innovation policy, and find out how its implications for the flow of foreign investment into Indonesia. This research uses online research methods (ORM) to discover new facts, information and conditions through technology and internet searches. The aspects used to conduct analysis in this descriptive qualitative research are using innovation policy instruments which include regulatory, economic, financial, and soft instruments. The research findings show that the golden visa as an innovation policy has great potential to support national development through investment in priority sectors. However, its implementation needs to be done carefully with strict supervision and inclusive regulations so as to mitigate risks such as money laundering and property price inflation. That way, golden visas can encourage sustainable and inclusive economic growth through the smooth flow of incoming foreign investment.