In this paper it is presented an improvement of the branch and bound algorithm for the permutation flow shop problem with blocking-in-process and setup times with the objective of minimizing the total flow time and tardiness, which is known to be NP-Hard when there are two or more machines involved. With that objective in mind, a new machine-based lower bound that exploits some structural properties of the problem. A database with 27 classes of problems, varying in number of jobs (n) and number of machines (m) was used to perform the computational experiments. Results show that the algorithm can deal with most of the problems with less than 20 jobs in less than one hour. Thus, the method proposed in this work can solve the scheduling of many applications in manufacturing environments with limited buffers and separated setup times.

The paper presents a fresh empirical approach for clarifying the impact of Jordan's most prevalent forms of ownership on the link between the “fair value (FV)” model share of assets and auditing costs. Using information gathered from 105 Jordanian financial listed companies spanning 2005 to 2018, ordinary least squares regression is applied in this paper. While financial institution ownership variables cause the opposite to be observed, family ownership decreases the link among the share of assets at FV and audit expenses. Family ownership results in decreased auditing costs paid only for “Level 1” assets; conversely, the extremely uncertain FV assets “Level 2 & 3” show the opposite. Financial institutional ownership demonstrates that auditing FV Level 1 leads to higher auditing costs. When relating FV Levels 2 and 3, the moderating effect of financial institutional ownership was significantly negative. No significant moderating effect of government ownership is confirmed. The inconclusive and limited empirical explanation of audit costs resulting from the FV model from a Western setting motivates our investigation. This study is considered as a unique study as it takes into account the most prevalent types of ownership in the Jordanian context in the FV studies reviewing auditees in Jordan. New evidence is generated by documenting audit characteristics of Jordan, a developing country, and its institutional environment and compliance with the FV model. The results are useful to regulators and policymakers in regulating the auditing profession and resolving FV audit-related conflicts and issues.

The rapid advancement of technology has substantially impacted numerous sectors, including the banking industry. It is now apparent that the banking industry is affected by the innovative role that the Internet of Things (IoT) plays, which affects a multitude of operations and services. This study uses a quantitative approach and PLS-SEM to investigate the widespread impact of Internet of Things (IoT) technology on the Excel Performance of Islamic Banks in the UAE. The study integrates the Resource-Based View (RBV), Islamic Banking Theories, and Fraud Triangle Theory to create a complete framework. The research's reliability is supported by a sample of 407 replies from 504 participants. The findings strongly support the hypotheses that IoT integration improves Islamic banking performance in the UAE, such as data analytics, customer service, automation systems, fraud detection capabilities, and asset-backed finance, while aligning with Sharia Principles and improving risk-sharing mechanisms. However, the influence of IoT on escalating fraudulent activities and hence negatively impacting performance was not proven. The study emphasizes the importance of IoT in improving operational efficiency and customer satisfaction in Islamic banks in the UAE.

An assignment problem (AP) usually deals with how a set of persons/tasks can be assigned to a set of tasks/persons on a one-to-one basis in an optimal manner. It has been observed that balancing among the persons and jobs in several real-world situations is very hard, thus such scenarios can be seen as unbalanced assignment models (UAP) being a lack of workforce. The solution techniques presented in the literature for solving UAP’s depend on the assumption to allocate some of the tasks to fictitious persons; those tasks assigned to dummy persons are ignored at the end. However, some situations in which it is inevitable to assign more tasks to a single person. This paper addresses a practical variant of UAP called k-cardinality unbalanced assignment problem (k-UAP), in which only of persons are asked to perform jobs and all the persons should perform at least one and at most jobs. The k-UAP aims to determine the optimal assignment between persons and jobs. To tackle this problem optimally, an enumerative Lexi-search algorithm (LSA) is proposed. A comparative study is carried out to measure the efficiency of the proposed algorithm. The computational results indicate that the suggested LSA is having the great capability of solving the smaller and moderate instances optimally.

This research aims to analyze the importance of Islamic Moderation (IM), which is the most prominent factor in the tourism attractiveness of the Kingdom of Saudi Arabia. This has made it an integrated and sustainable tourism destination throughout the year. The study applies a quantitative survey method and selects a probability sample of 470 questionnaires to collect data in the Jeddah region of the Kingdom of Saudi Arabia, using a probability sampling method. After employing purposive sampling to select the participants, a structural equation model (SEM) is employed to analyze the data. The proposed theoretical framework is utilized to examine the mediating role of Islamic Destination Image (IDI), in the correlation between Islamic Moderation (IM) and Destination Attractiveness (DA). Upon revisiting previous research, the study discovers several studies that concentrate on the concepts, mechanisms, and characteristics of moderation, the significance of disseminating moderate thought, addressing extremist thought, and its impact on the economy and international and regional relations. An examination of the total effect yields the conclusion that Islamic Moderation (IM) has a positive impact on Destination Attractiveness (DA); this effect is both positive and strong, both directly and indirectly. The Islamic Moderation (IM) has a significant, positive, and significant impact on the Islamic Destination Image (IDI).

The leaching of two pesticides, cholantraniliprole (CAP) and bispyribac-sodium (BPS) in sandy clay loam soil (soil A) and sandy loam soil (soil B) were examined, by soil columns under laboratory conditions. In addition, the effect of adding 5% biochar and wheat straw to the soils on the leaching of CAP and BPS was studied. It is clear from the results that BPS is more leachable than CAP in all soil columns, and more leached to soil B. It was found that the addition of biochar and wheat straw has a significant effect on the movements of these pesticides and can be used to reduce the environmental impact. For CAP, 71 to 97% and 84 to 97% were recovered from the soil A columns and soil B columns, respectively, while for BPS, 94 to 99% were recovered from columns of soil A and soil B.

This document addresses the problem of scheduling and routing a specific number of vehicles to visit a set of customers in specific time windows during a planning horizon. The vehicles have a homogeneous limited capacity and have their starting point and return in a warehouse or initial node, in addition, multiple variants of the classic VRP vehicle routing problem are considered, where computational complexity increases with the increase in the number of customers to visit, as a characteris-tic of an NP-hard problem. The solution method used consists of two connected phases, the first phase makes the allocation through a mixed-integer linear programming model, from which the visit program and its frequency in a determined plan-ning horizon are obtained. In the second phase, the customers are grouped through an unsupervised learning algorithm, the routing is carried out through an Ant Colony Optimization metaheuristic that includes local heu-ristics to make sure com-pliance with the restrictive factors. Finally, we test our algorithm by performance measures using instances of the literature and a comparative model, and we prove the effectiveness of the proposed algorithm.

Supply chain management (SCM) that is Lean, Agile, Resilient, and Green (LARG) are required for competitiveness in today's complex, high-demand market. SCM must consider LARG paradigms concurrently, a rarely investigated topic. This study provides a comprehensive review of publications that combine all four LARG principles in engineering, business, and management domains. According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach, two Scopus and Google Scholar databases were exhaustively examined. Thirty-two manuscripts were selected for a comprehensive review. The year of publication, document type, countries, authors, journals, keywords, and topics was analyzed from 2000 to 2023. Also, each paper's methodology, central topic, findings, limitations, and future recommendations were outlined. Consequently, the current systematic literature review (SLR) revealed that the proposed topic is in its infancy, with promising prospects. By emphasizing the findings of this study, managers and businesses can increase consumer satisfaction and reduce costs.

Rhodanines are recognized as privileged heterocycles in medicinal chemistry. The main achievements include the development of drug-like molecules with numerous biological activities as well as approved drugs. The Furan nucleus is considered one of the promising heterocyclic cores in medicinal chemistry that showed numerous ranges of activity. The combination of several heterocycles in a one molecule commonly provides much more interest in the enhanced activity profile of its analogs than their parent separate constituents. Such conjugates are promising objects for modern medicinal chemistry. In this review paper recent advances in the synthesis and biological activities rhodanine-furan conjugates which its application in the different field of drug discovery.

The global investment landscape has undergone a paradigm shift, focusing on Environmental, Social, and Governance (ESG) factors as the major determinants of financial sustainability in investment decisions worldwide. This study uses predictive modeling to analyze the complex link between ESG variables and investment decisions. Focusing on three key sectors: IT, FMCG, and BFS, the study adopts a predictive modeling approach, recognizing the distinct characteristics and challenges within each sector. The information depends on the data obtained from different places like ESG details, and previous financial performance pointers – EBITDA, EPS, ROE, and P/E for 2018 to 2022, inclusive of general investor behavior. We can do this by working with relevant sources of data together with machine learning methods which show what happens in the Indian market in terms of ESG influencing the market thus leading to sustainable investment outcomes. This article seeks to comprehend why investors may favor sustainability as opposed to their conventional monetary units.