The primary objective of this study is to explore numerical techniques for solving intuitionistic fuzzy wave equations, with a focus on applying this approach to bridge suspension cables or strings. Existing intuitionistic fuzzy finite difference methods suffer from the explicit nature of finite differences, leading to conditionally stable solutions. Additionally, most of the uncertainty in the literature is based on the classical fuzzy set. This study extends the explicit fuzzy finite difference scheme to the intuitionistic implicit fuzzy finite difference method for solving intuitionistic fuzzy wave equations. The proposed method uses the second-order finite difference method to approximate the wave equation in implicit form. The initial and boundary conditions of the wave equation are described using intuitionistic triangular fuzzy numbers. The error analysis, consistency, convergence, and stability of the scheme are rigorously analyzed to ensure mathematical reliability. A representative problem from engineering applications, such as analyzing a bridge cable under wind loading, has been solved. To demonstrate the method's practicality, the numerical results are compared with the exact solution. By stability analysis, the method is found to be unconditionally stable. The findings confirm that the proposed approach approximates the solution with high accuracy, making it a significant contribution to numerical methods for solving intuitionistic fuzzy wave equations in real-world applications.
This study presents a comparative numerical analysis of four chaotic map-based strategies for solving Optimal Control Problems (OCPs). The proposed framework involves a two-phase process: first, OCPs are discretized and reformulated as nonlinear optimization problems; subsequently, optimization is performed using the Logistic Chaotic Reduction (LCR), Improved Logistic Chaotic Reduction (ILCR), Logistic Chaotic Reduction with Gradient Search, and Chaotic Gradient-based Optimization (CGO) algorithms. To evaluate performance, five benchmark problems are examined. Among the methods tested, CGO demonstrates superior convergence speed and solution precision. Numerical results show that integrating chaotic dynamics with gradient-based search effectively balances exploration and exploitation, mitigates premature convergence, and improves numerical accuracy. A comparative analysis with conventional techniques across multiple test cases further confirms the computational efficiency and robustness of CGO. These findings position chaotic optimization as a viable and competitive alternative to traditional gradient-based and heuristic approaches in solving OCPs.
Food waste in Vietnam’s food service sector poses significant economic, environmental, and social challenges. This study uses an integrated grey Delphi and Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach to identify critical factors contributing to food waste. An initial list of factors was identified from existing literature and further refined through expert evaluation using the Grey Delphi approach. Sixteen experts were selected for the panel based on their background and professional experience. Finally, 34 valid factors were identified as valid and arranged into six major groups: Purchasing, receiving, inventory control, preparing, selling, and general drivers. These factors were then analyzed using grey DEMATEL to map causal relationships and influence strengths. The findings highlight improper inventory management, inaccurate demand forecasting, and limited customer awareness as key drivers requiring managerial focus. This research introduces a novel application of grey theory to address complex, data-scarce problems, offering a robust framework for analyzing food waste. By delineating the origins and pathways of waste propagation, the study provides actionable insights for managers to enhance sustainability and reduce waste in Vietnam’s food service industry.
Quality management in the garage service sector is a major issue in Ethiopia for both businessmen and customers. To improve the service quality management system and determine the best option, a model has been developed that integrates MCDM techniques with the service quality management model. The different service quality management models, including the Gummesson 4Q, have been considered in previous literature; however, their integration with the FTOPSIS methodology has not been studied. In filling this gap, in this research, firstly literature review regarding the service quality management models and MCDM tools, including FTOPSIS, has been conducted to depict the areas in which the models are applied. Second, among the models, due to its nature of providing high-quality service quality management opportunities, Gummesson’s 4Q model, with its dimensions, namely designed quality, product quality, delivery quality, and relational quality, was selected for this study as the comparison criteria. Finally, an FTOPSIS methodology was applied to prioritize garage service providers. According to the methodology, the results showed that A1, A5, and A4 are the best garage service providers with the Closeness Coefficients (CC) of 0.469, 0.466, and 0.458, respectively. As the main implication and contribution, the research procedures, framework, model, and obtained results using the developed methodology can help the sector investors adjust their internal resource capacity toward ascertaining the required service quality, and for end customers to perceive quality and a high level of satisfaction. Explicitly, the managerial implications of this study are defined as its importance for strategic decision making, enhancing customer satisfaction, guiding resource allocation, and providing quality improvement initiatives. In addition, it is also helpful for practitioners, academicians, researchers, and policy makers to determine the service quality through the designed management system to provide a possible solution within the sectors and similar sectors.
This paper examines the impact of Financial Knowledge (FK), Parental Influence (PI) and exposure to financial education on Financial Behavior (FB) of university students and the role of Financial Self-Efficacy (FSE) in mediating the impact. Recent causal and meta-analytic findings indicate that properly-designed financial education programs can enhance knowledge and downstream behavior, but the mechanism by which the process works, particularly the role of FSE in transforming inputs into action, has not been specified in terms of student populations. Socialization in the family setting and new randomized evidence found in school-based curricula are the basis of a unified model tested with FSE as intermediate. Methodology: a cross-sectional survey of N students was carried out at. FK, PI, exposure to education and FSE, and FB were measured with a set of items that were validated. The quality of measurement was determined through Confirmatory Factor Analysis (CFA) (α, CR, AVE, HTMT). Direct and indirect mediation were estimated using structural equation modelling; mediation was tested using bias-corrected bootstrapping (5,000 resamples). Adequacy of the model was evaluated using 3 metrics which are 2/df, cfi, RMSEA and SRMR. (complete items and eligibility criteria are found in methodology). Direct impacts on FB were positive and significant in the case of FK, PI and exposure to education. FSE had a positive relationship on behavior and mediated the effects of each antecedent. The trend aligns with: 1) meta-analytic data that financial education enhances behaviors, 2) family-socialization studies that adhered to the observed parental behaviors and FB in early adulthood, and 3) behavioral results identifying efficacy/confidence as a proximal driver of favorable FB. Findings predate FSE as a process that links instruction, knowledge and family socialization with behavior of students. As practice, schools are recommended to combine curriculum and efficacy-building activities (guided practice, feedback, goal-tracking), parent engagement, and teacher professional development. Recent school-based randomized evidence favors the viability of this type of programmatic design. Recommendations: 1) incorporate mandatory, sequenced literacy units, 2) introduce parent-student workshops, based on budgeting and saving, 3) offer educator toolkits and PD associated with efficacy-building, and 4) implement behavior dashboards, as a monitoring and customized assistance tool. Cross-sectional, self-report data limit causal inference; replication with longitudinal or multi-site samples is recommended.
