In this manuscript, we delve into the realm of lattice ordered complex linear diophantine fuzzy soft set, which constitutes an invaluable extension to the existing Fuzzy set theories. Within this exploration, we investigate basic operations such as \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} $\oplus$\end{document}⊕ and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} $\otimes$\end{document}⊗, together with their properties and theorems. This manuscript is more amenable in two ways, i.e., it enables real-life problems involving parametrization tool and applications with an existing order between the components of the parameter set based on the preference in the complex frame of reference. Adaptive cruise control (ACC) is a system designed for maintaining distance between two vehicles and to sustain a manually provided input speed. The purpose of cars with ACC is to avoid a collision that frequently happens nowadays, thereby improving road safety regulations amidst rising collision rates. The fundamental aim of this manuscript is to prefer an applicable car with ACC together with its latest model by defining a peculiar postulation of lattice ordered complex linear diophantine fuzzy soft set \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} $\rm ( \widehat{LOCLDFSS} )$\end{document}(LOCLDFSS^). Emphasizing real-life applicability, we illustrate the effectiveness and validity of our suggested methodology in tackling current automotive safety concerns, providing useful guidance on reducing challenges related to contemporary driving conditions.

This paper addresses the concept of the vendor-managed inventory (VMI) problem, focusing on the replenishment policy and the vehicle routing problem (VRP) model. These components are integrated to tackle a three-echelon distribution issue comprising a single plant, multiple depots, and multiple retailers, with the primary objective of minimizing transportation and inventory costs within this complex distribution network. A three-phase methodology is proposed to optimize the entire supply chain, from the plant to the final retailer, and its performance is evaluated through computational experiments. This research is motivated by a real-life supply network, highlighting its practical relevance and applicability. To extend the capabilities of existing methods for solving the combined inventory and routing problem, an insertion heuristic is incorporated to enhance vehicle utilization, thereby reducing total costs. Computational results demonstrate the effectiveness of the improved algorithm, indicating that it is sufficiently robust for practical application. Significant cost savings can be achieved with the proposed approach, making it a valuable contribution to the field of supply chain optimization.

The eternal 1-secure set, strategically protects graphical structures against attacks by placing sentinels within dominating sets. This study adapts this concept to real-world scenarios, like emergency response systems, by addressing challenges such as roadblocks and traffic congestion. We introduce the secure set and the eternal 1-secure set for fuzzy graphs based on edge membership levels J. Our analysis examines the relationship between the security number of a fuzzy graph G at level J and the domination number of its spanning subgraph at level J, demonstrating the potential of the eternal 1-secure set to enhance security measures in dynamic environments.

Enterprise resource planning (ERP) is widely used to boost the total market power of businesses. The wrong selection is one of the key reasons why ERP installations fail. Due to the complexity of the business environment and the range of ERP systems, choosing an ERP system is a complex and time-consuming procedure. ERP alternatives may be assessed using several criteria, so the ERP selection process may be considered a multi-criteria decision-making (MCDM) problem. In this study, the rough best worst method (BWM) was used to determine criteria weights, while the newly developed rough integrated simple weighted sum product (WISP) was used to rank ERP alternatives. Results suggest that the SFT-4 coded software is regarded as the best option, followed by SFT-5, SFT-6, SFT-2, SFT-3, and SFT-1. Results of the newly developed rough WISP method are compared to those of existing rough techniques in the sensitivity analysis. The differences between them have been found to be negligible. The outcomes show how effectively developed rough BWM and WISP integrated method performs in terms of ERP selection with usability, accuracy, ease of use, and consistency. This study will help decision-makers in a context where ERP is implemented choose the best ERP software for different sectors.

The expansion of the open-pit exploitation of mineral raw materials, and especially the energy resources of fossil fuels, makes open-pit coal mines spatially dominant objects of large mining basins. Exploitation activities are accompanied by negative ecological impacts on the environment, which requires the integral planning, revitalization, reclamation, and rehabilitation of the disturbed area for human use in the post-exploitation period. The post-exploitation remediation and rehabilitation of open-pit mining areas and disposal sites, i.e., space disturbed by mining activities and accompanying facilities, are complex synthetic multidisciplinary multiphase engineering project tasks. In this paper, a hybrid fuzzy MCDM model (Multiple-Criteria Decision-Making) was developed for the selection of a reclamation solution for the Tamnava-West Field open-pit mine. IMF SWARA (Improved Fuzzy Stepwise Weight Assessment Ratio Analysis) was applied to define the weights of 12 criteria of different structures used in the evaluation of reclamation solutions. The Fuzzy ROV (Range of Value) method was applied to select the reclamation solution from a total of 11 solutions previously obtained using a process approach. The results of the hybrid IMF SWARA—Fuzzy ROV model show that forestry is the best solution for the Tamnava-West Field open-pit mine. After the results had been obtained, verification analyses of the proposed model were performed and the best stable proposed reclamation solution was determined.

ABSTRACT

: The escalating migration from rural to urban locales necessitates an augmented demand for the workforce, local utility services, and mechanization to sustain a balance conducive to public health. This investigation delineates the pivotal role of human resources in executing daily operations required for the upkeep of public green and asphalted areas within Doboj, Bosnia and Herzegovina. It is posited that teamwork and the requisite competencies of the workforce are integral to the utility company’s efficacy and the establishment of conditions requisite for addressing business tasks delineated on weekly and monthly schedules. A cohort of 20 personnel, tasked with the aforementioned responsibilities, was segmented into three categories, predicated upon their skills and capability to fulfil the designated tasks within specified temporal bounds. A novel hybrid Multi-Criteria Decision-Making (MCDM) model, integrating Improved fuzzy Stepwise Weight Assessment Ratio Analysis (IMF SWARA) with Measurement Alternatives and Ranking according to Compromise Solution (MARCOS), was employed to appraise employees across the designated categories. Decision-makers articulated five criteria, which were quantified via the IMF SWARA methodology. Subsequently, the appraisal of worker categories through three discrete models was undertaken employing the MARCOS technique. Outcomes for each category were individually derived and subjected to verification tests, revealing that criterion significance markedly influences human resource ranking. This study underscores the crucial intersection between environmental stewardship and human resource management, advocating for a systematic approach to urban maintenance that leverages MCDM techniques to optimize workforce performance.

The capacity of transport infrastructure is one of the very important tasks in transport engineering, which depends mostly on the geometric characteristics of road and headway analysis. In this paper, we have considered 14 road sections and determined their efficiency based on headway analysis. We have developed a novel interval fuzzy-rough-number decision-making model consisting of DEA (data envelopment analysis), IFRN SWARA (interval-valued fuzzy-rough-number stepwise weight-assessment-ratio analysis), and IFRN WASPAS (interval-valued fuzzy-rough-number weighted-aggregate sum–product assessment) methods. The main contribution of this study is a new extension of WASPAS method with interval fuzzy rough numbers. Firstly, the DEA model was applied to determine the efficiency of 14 road sections according to seven input–output parameters. Seven out of the fourteen alternatives showed full efficiency and were implemented further in the model. After that, the IFRN SWARA method was used for the calculation of the final weights, while IFRN WASPAS was applied for ranking seven of the road sections. The results show that two sections are very similar and have almost equal efficiency, while the other results are very stable. According to the results obtained, the best-ranked is a measuring segment of the Ivanjska–Šargovac section, with a road gradient = −5.5%, which has low deviating values of headways according to the measurement classes from PC-PC to AT-PC, which shows balanced and continuous traffic flow. Finally, verification tests such as changing the criteria weights, comparative analysis, changing the λ parameter, and reverse rank analysis have been performed.

Abstract By providing important indicators, financial indices help investors make educated judgements regarding their assets, much like vital sign monitors for the financial markets. The best way for investors to keep up with the market and make strategic adjustments is to keep an eye on these indexes. Researching the most important financial indexes for making educated investing decisions is, thus, quite relevant. Finding the most essential financial indices from an investing standpoint and assigning a weight to each of those indexes are the main goals of this research. A weighted score is derived by combining four financial indices in a Multi-Criteria Decision-Making (MCDM) technique. These objectives are then pursued. Triangular Fuzzy Numbers (TFNs) and the Fuzzy Analytic Hierarchy Process (F-AHP) are used to determine the weights of criteria in this technique. Using these methods together, the research hopes to provide a thorough analysis of the role that different financial indexes have in informing investment choices. This study emphasizes the paramount importance of considering the Price Earning to Growth (PEG) ratio when making investment decisions, followed by the Debt Equity Ratio. Price to Book Value and Dividend Yield, while relevant, carry comparatively less weightage in the overall assessment. Investors are advised to use these insights as a guideline in their financial analysis and decision-making processes.