Decision-making Issues Research Articles

Mathematical Modelling Of Municipal Solid Waste Management In Spherical Fuzzy Environment

A Spherical fuzzy model induced with teaching learning based optimization technique is developed for supporting the municipal solid waste management under fuzzy environment. Spherical fuzzy set’s ability to capture imprecise and contradictory information results in a substantial contribution to decision-making issues. Thus, we introduce SFLPP in a spherical fuzzy environ-ment in this article, which entails maximization of truthiness and minimization of indeterminacy and falsity membership functions.In present era TLBO is gaining the popularity of being less complex and only two algorithmic parameters based algorithm. This study introduced a mathematical model to include all of the major components of municipal solid waste management. To deal with uncertainty, the mathematical model of municipal solid waste management is defined using a spherical fuzzy environment.The goal of this research is to determine the current state of waste management in the Dinanagar area of Punjab, India. Finally,the mathematical model is in possession of long-term waste management in the study area, Dinanagar city in Punjab, India. The findings of comparing the suggested model to the current framework show that the new model provides better solutions in terms of sustainability.

Commercial Aircraft Selection Decision Support Model Using Fuzzy Combinative Multiple Criteria Decision Making Analysis

Multidimensional decision-making issues invariably entail a profusion of factors and dimensions necessitating consideration. In such intricate environments, decision-making can be notably challenging. To navigate this complexity, the realm of multiple criteria decision-making approaches is indispensable, helping in unraveling convoluted predicaments. This paper introduces a novel approach fuzzy combinative multiple criteria decision-making analysis — crafted to address fuzzy decision analysis challenges. At the heart of this method lies the utilization of the Euclidean distance as the primary measure and the rectilinear distance as the secondary measure, both calibrated in accordance with the negative-ideal solution. Determining the desirability of alternatives rests on these distances. Further augmenting the evaluation, the process involves combining the Euclidean and rectilinear distances through fuzzy combinative multiple criteria decision-making analysis. The efficacy and stability of the fuzzy decision analysis are underscored through a numerical example, illustrating the proposed method's procedural nuances. A comparative analysis comparing both Euclidean distance and rectilinear distance with the weighted sum model and the weighted product model is also conducted. This scrutiny underscores the efficiency of the proposed method while affirming the reliability of its outcomes.

Pelaksanaan Putusan Eksekusi BANI atas Sengketa Kontrak antara Badan Layanan Umum BP3TI dengan PT. Indonesia Comnets Plus dan Konsorsium NIPRESS

The Indonesian National Arbitration Board (BANI) is an option in resolving contract disputes between the government and private parties. When the government is in a losing position in a contract dispute according to the BANI decision, the government must comply with the BANI decision. This study aims to understand the implementation of the execution of BANI decisions that conflict with Law Number 1 of 2004 concerning State Treasury and the authority of the Supreme Court to address the issue of BANI decisions that conflict with Law Number 1 of 2004 concerning State Treasury. The focus of this research includes the execution of BANI decisions that are contrary to Law Number 1 of 2004 concerning State Treasury and the Authority of the Supreme Court to the Court that confiscates state assets. The research method used in this research is normative juridical through statutory and conceptual approaches using secondary legal data consisting of primary legal materials, secondary legal materials and tertiary legal materials. The data obtained from library research is then analyzed using descriptive qualitative. Based on the research, it is found that the execution of the BANI decision carried out by the court through the confiscation of a sum of money in an account belonging to the BP3TI Public Service Agency should not be carried out because this has contradicted Article 50 of Law Number 1 of 2004 concerning State Treasury. Therefore, the Supreme Court is expected to play a role in providing solutions by providing guidance to the lower courts including the district courts by issuing a Supreme Court Circular Letter (SEMA).

Theoretical Approaches Before the Adoption of Administrative Decisions in the Area of Public Administration

The article is devoted to the problem of researching theoretical approaches to the process of making managerial decisions in the field of public administration. It is noted that considering the process of making managerial decisions as an object of public management, it is emphasized that the decision-making process is multi-level. Such are the models and concepts on the basis of which decision-making can be explained, and which are multidimensional and interdisciplinary in their content. It is important to emphasize that decision-making is often perceived as a deliberative process that can be both rational and irrational, based on well-stated or only implicit assumptions Most scientific sources present a traditional linear concept of decision making, in other words, a sequence of steps is presented that helps the decision maker to make the best decision. There are many formal decision-making models, but it can be argued that the basis of managerial decision-making theories are the three most important and widely known theories of such decision-making, which emphasize the intellectual activity of decision-makers and the procedural aspect - the theory of rational complexity, the theory of incrementalism and mixed scanning theory. Touching upon the conditions and criteria of the managerial decision-making process in public administration, it is worth noting that there are many theories of decision-making, most of which have a descriptive element, that is, how decisions should be prepared, and normative guidance on how decisions should be made. Each of these approaches offers a framing mechanism and describes fundamental decision-making issues. Thus, the preparation of decisions in public administration is directly related to legislation, as they are limited and influenced by various factors and conditions, therefore absolutely objective decisions do not exist in public administration, there are only less subjective and more subjective decisions . It was concluded that management decision-making is one of the most difficult issues in the process of functioning of public administration, since management decision-making is influenced by many different factors and processes. Most of the models that explain management decision-making are descriptive and aim to emphasize the quality of information processing necessary for management decision-making. No single method of managerial decision-making can be singled out as the best, because different circumstances, different values of those who make managerial decisions, different goals or methods of managerial decision-making, and the situation in an organization or institution are different in each situation. It can be argued that rational or stepwise management decision-making methods are better in some situations, and mixed-scan management decision-making methods or a combination thereof in others.

A large-scale group decision-making model considering risk attitudes and dynamically changing roles

Aiming at three issues in large-scale group decision-making (LSGDM): risk attitudes, dynamically changing roles, and dynamically adjust evaluation information of decision makers (DMs), this paper constructs an LSGDM model by considering risk attitudes and dynamically changing roles. Firstly, we introduce the concept of risk attitudes and the method of identification and creatively combine it with Decision Making Trial and Evaluation Laboratory to divide DMs into four categories including core DMs, driven DMs, independent DMs, and followers. Considering the dynamically changing roles of DMs, an adjustment method for evaluation information is proposed. Then a double recognition mechanism is developed to determine whether the consensus has been reached. Moreover, we construct a method to determine the weights of DMs. Based on the above research, an LSGDM model based on probabilistic double hierarchy linguistic term set is constructed and applied to a practical problem of the selection of emergency medical distribution schemes. Finally, a sensitivity analysis is performed to examine the impact of different adjustment coefficients on the results, and the validity of our method is further illustrated by comparative analysis.

Intelligent framework for multiple-attribute decision-making under probabilistic neutrosophic sets and its applications

Highway engineering itself is a large-scale project with high construction safety requirements, involving multiple construction safety factors. In order to better ensure the orderly development of highway tunnel construction, it is necessary to strengthen construction safety evaluation. The construction safety management evaluation of highway engineering is viewed as the multiple-attribute decision-making (MADM) issue. In this paper, an extended probabilistic neutrosophic number TOPSIS (PNN-TOPSIS) method is established for construction safety management evaluation of highway engineering. The PNN-TOPSIS method integrated with CRITIC method in probabilistic neutrosophic sets (PNSs) circumstance is applied to rank the optional alternatives and a numerical example for construction safety management evaluation of highway engineering is used to proof the newly proposed method’s practicability along with the comparison with other methods. The results display that the approach is uncomplicated, valid and simple to compute.

Improving computer network security evaluation with grey relational analysis and probabilistic simplified neutrosophic sets

The popularity of computer network has provided great convenience for people’s work and life, but it has also brought corresponding information security problems. It is very important to do a good job in computer network security evaluation. Conventional computer network security evaluation can be realized with the help of firewalls, antivirus software, etc., while in the face of complex computer network applications, it is necessary to adopt a security evaluation method with good operability and wider application range. The computer network security evaluation is viewed as multiple attribute decision-making (MADM) issue. In this paper, an extended probabilistic simplified neutrosophic number grey relational analysis (PSNN-GRA) method is established for computer network security evaluation. The PSNN-GRA method integrated with Criteria Importance Though Intercrieria Correlation (CRITIC) method in probabilistic simplified neutrosophic sets (PSNSs) circumstance is applied to rank the optional alternatives and a numerical example for computer network security evaluation is used to proof the newly proposed method’s practicability along with the comparison with other methods. The results display that the approach is uncomplicated, valid and simple to compute.

Modeling economic-environmental-ecological trade-offs for non-point source control strategies: A case study of Dianchi lake watershed, China

Non-point source (NPS) pollution has become a primary threat to the water environment. With the implementation of numerous control projects, striking a balance between economic costs and efficiency has become an urgent issue for decision-makers. To identify the optimization solutions for best management practices (BMPs) at the watershed scale, a genetic algorithm and the Soil and Water Assessment Tool (SWAT) model were combined to evaluate the trade-offs of NPS control strategies. The BMPs considered in this model included soil testing and fertilizer application technology, integrated pest management projects, conservation tillage, lakeside belt ecological construction, forest construction, and vegetation filter strips. The decision variables are the type and size of the BMPs, with the objective of minimizing costs while simultaneously maximizing both total phosphorus (TP) reduction and ecosystem service value. TP reduction was simulated usinga calibrated SWAT model that successfully assessed NPS pollution in the Dianchi lake watershed. Considering NPS generation and transfer, three NPS control scenarios were designed: source reduction, process retention, and integrated control. The upper limits of the costs for three scenarios were 157, 4921, and 5013 million yuan, respectively. It is suggested that the ecological benefits should be taken into account in the BMPs design. This finding is conducive to generating optimized control schemes that can effectively balance the trade-offs between socioeconomic costs and environmental sustainability.

Enhancing decision-making framework for talent cultivation quality evaluation using dual Hamy mean and prioritized aggregation operators

At present, the solidification of disciplines and majors in higher education, unclear training objectives, and the need to strengthen teacher information literacy are practical problems that constrain the optimization of the “artificial intelligence+” talent training model. Scientifically adjusting training objectives, upgrading the “artificial intelligence+” talent training model in higher education by integrating multi-disciplinary curriculum systems, strengthening school enterprise cooperation, industry education integration, establishing credit recognition mechanisms and diversified evaluation mechanisms. The quality evaluation of “Artificial Intelligence+” talent cultivation in higher education in the era of education informatization 2.0 is looked as the multiple-attribute decision-making (MADM) issue. In this paper, we extended the dual Hamy mean (DHM) operator and prioritized aggregation (PA) operator to 2-tuple linguistic neutrosophic sets (2TLNSs) to propose the 2-tuple linguistic neutrosophic prioritized DHM (2TLNPDHM) operator. Finally, a decision example for quality evaluation of “Artificial Intelligence+” talent cultivation in higher education in the era of education informatization 2.0 is employed to show the 2TLNPDHM operator. The main contributions of this study are summarized: (1) the 2TLNPDHM operator is built; (2) the 2TLNPDHM operator is designed to cope with the MADM with 2TLNNs; (3) an empirical real-life example for quality evaluation of “Artificial Intelligence+” talent cultivation in higher education in the era of education informatization 2.0 is supplied to proof the designed method; (4) some comparative decision studies are used to show the rationality of the 2TLNPDHM.

Managing a sustainable dual-channel supply chain for fresh agricultural products using blockchain technology

The use of blockchain technology in the supply chain for fresh agricultural products (FAP) is becoming an issue for decision-makers who want to improve control and performance. Blockchain can give consumers real information about a product, which is good for building trust in a brand. However, its profits and associated costs must be well-adjusted when executing blockchain solutions. This study looks at a two-step FAP supply chain with only one retailer and one producer. The FAP is produced and processed by the manufacturer, who then supplies it to the retailer. The manufacturer simultaneously operates an online/e-tail channel to sell its product. The company gives consumers the right certificates using sustainable organic production and green packaging. End consumers' demand is based on the retail price, the e-tail price, how fresh the product is, how long it takes to check the quality level, and how real the green certificates are. Two models of decentralized decision-making are created to investigate the execution criteria of blockchain technology. A centralized decision-making model with blockchain technology is also being developed to get the best channel performance. We use subgame-perfect equilibrium to resolve channel conflict and for coordination. Then, extended alternative offer bargaining is suggested as a way for the retailer and the manufacturer to decide how to split the extra money. Finally, a numerical example depicted that although blockchain technology benefits the supply chain members, consumers have to pay more to get the service. It is also found that if a firm can form and maintain a trustworthy atmosphere for its FAP then it may continue its business without implementing the blockchain.

Using discrete-event simulation to assess an AHP-based dynamic patient prioritisation policy for elective surgery

ABSTRACTPatient prioritisation in elective surgery is a critical multi-criteria decision-making issue. Elective patients should be ranked on the waiting list based on various criteria related to their health conditions and their evolution over time. This study suggests a dynamic prioritisation where elective patients are ranked considering their evolving health conditions, waiting time, and patient loss, i.e., the likelihood of patients abandoning the waiting list. We proposed deploying the Analytic Hierarchy Process (AHP) to weigh prioritisation criteria. The AHP-derived weights are integrated into a discrete-event simulation model, which periodically ranks patients considering their health status, waiting time, and patient loss. The proposed dynamic prioritisation is compared with the first-come, first-served (FCFS) policy and the static prioritisation, which ranks patients according to their initial priority. Results showed that dynamic prioritisation outperforms the FCFS and static prioritisation policies in preventing health deterioration, reducing weighted waiting time, and reducing the ratio of lost patients.

Prospect theory-based large-scale group decision-making method with heterogeneous preference relations

Large-scale group decision-making (LSGDM) issues are increasingly prevalent in modern society across various domains. The preference information has emerged as a widely adopted approach to tackle LSGDM problems. However, a significant challenge lies in facilitating consensus among decision-makers (DMs) with diverse backgrounds while considering their hesitation and psychological behavior. Consequently, there is a pressing need to establish a novel model that enables DMs to evaluate alternatives with heterogeneous preference relations (HPRs). To this end, this research presents a new consensus-building method to address LSGDM problems with HPRs. First, a novel approach for solving collective priority weight is introduced based on cosine similarity and prospect theory. In particular, a new cosine similarity measure is defined for HPRs. Subsequently, a consensus index is provided to gauge the consensus level among DMs by considering their psychological behavior and risk attitudes. Further, a consensus-reaching model is developed to address LSGDM with HPRs. Finally, an instance of supplier selection is presented to demonstrate the practicality and efficacy of the proposed method.

교수의 자유에 대한 제한과 그 한계

This paper attempted to identify the possibilities and limits of restrictions on the freedom of professor’s lecturing, which is a constitutional right under the Korean Constitution, through a commentary on the Supreme Court's 2014Do3923 decision.
 The core issue of the 2014Do3923 decision commented in this paper is whether the professor's conduct of lecturing by distributing press articles unfavorable to a presidential election candidate as part of the lecture content and method can be considered a violation of the Public Official Election Act, in relation to academic freedom, especially the freedom of professor’s lecturing.
 Among academic freedoms, which are constitutional rights guaranteed under the Korean Constitution, there is little in-depth prior research on the scope or degree of protection, restrictions, and limits on the freedom of professor’s lecturing.
 The significance of the Supreme Court's 2014Do3923 decision is summarized as follows.
 First, this decision is significant as the first Supreme Court’s ruling regarding restrictions on the freedom of professor’s lecturing and its limits. In particular, there were almost no court rulings or decisions of the Constitutional Court that directly address the relationship between the freedom of professor’s lecturing and positive law or deal in depth with the content, possibility of restrictions, and limits of the freedom of professor’s lecturing. In this respect, the Supreme Court's 2014Do3923 decision directly addresses the relationship between the freedom of professor’s lecturing and the Public Official Election Act, and argues in depth the content of the freedom of professor’s lecturing, the possibility of restrictions, and its limits. It can be positioned as the ‘first’ Supreme Court ruling that ‘directly’ addresses the possibility of restrictions, and its limits.
 Second, the legal principles regarding the restrictions on the freedom of professor’s lecturing and their limits presented in this ruling can present theoretically and practically meaningful judicial judgment standards in actual cases related to the freedom of professor’s lecturing in the future.

INFORMATION SOURCES OF TRADING DECISION MAKING AS DETERMINING FACTORS FOR COGNITIVE BIASES

In the article the issues of trading decision making are being discussed in the lights of cognitive biases in uncertainty. The process of trading stocks requires buy/sell decision making in uncertain conditions under extreme time constraints. In ever-changing market decisions are made momentarily and cognitive biases and heuristics determine the speed and quality of decisions. Information and expectations are the core of cognitive component of the process and can influence biases.

Docked Bikeshare Equity and Goal Conflict: An Evaluation Using Gini Coefficients and Lorenz Curves

The equitable distribution of docked bikeshare is an important issue for transportation decision-makers. Gini coefficients and Lorenz curves can be used to study transportation inequality. This study used these methods to achieve three outcomes. First, this study identified a gap in bikeshare equity literature and provided a more nuanced measure of bikeshare supply to better evaluate how well bikeshare meets demand. Second, the updated measure of distributional equity was used to evaluate bikeshare equity in Washington, DC. Third, using historical trip data, the Gini coefficient calculations indicated which trip types are better served. Comparison of the results highlighted a potential conflict in program goals: equity versus supporting existing bikeshare members. Policy feedback may bias this trade-off in favor of members, reinforcing spatial inequalities. Overall, this paper further demonstrated how Gini coefficients and Lorenz curves can be useful tools for evaluating inequality in transportation systems.

Uncertainty and decision-making with multi-polar interval-valued neutrosophic hypersoft set: A distance, similarity measure and machine learning approach

The issue of decision-making (DM) is intricate due to the environment's ambiguous, imprecise, and uncertain nature, particularly when multiple attributes are involved and further subdivided. To address such complex problems, the concept of the hypersoft set has been employed. This article shows how to combine the multi-polar interval-valued neutrosophic set with the hypersoft set. This can help you solve DM problems that have more than one attribute. Additionally, we define similarity measures for multipolar interval-valued neutrosophic hypersoft sets (mPIVNHSs). We discuss the proposed extensions' definitions and mathematical operations and present an algorithm to solve DM problems related to everyday life using the proposed operators under mPIVNHSs. A machine learning method called K-Nearest Neighbor (KNN) is also employed to calculate ranking in the selection of sites for a new store. By utilizing the potential of data point similarity, K-Nearest Neighbors (KNN) and similarity measurements have practical value in daily life. KNN mimics the human propensity to draw from related experiences, resulting in applications like customized suggestions. Parallel to this, similarity metrics statistically evaluate resemblance to support tasks like personalized advice across fields like biology and social networks. Finally, we conclude the present study by comparing it with the existing studies, and future directions are also given.

Analysis of the Game Behavior of Real Estate Mortgage Securities Issuers Based on Reciprocal Preferences

In recent years, the Chinese government has gradually begun to pay attention to the development of real estate investment trusts (REITs) and hopes to use REITs to increase the securitization of assets in the real estate market, making it possible to accelerate the circulation of funds in the real estate market. In order to enable issuers to price REITs effectively to form a mutually beneficial transaction model with investors, to increase the willingness and success rate of both parties and to ultimately create a harmonious and efficient REITs market, it is important to study the pricing decisions of issuers when issuing REITs. This study analyzes and investigates the issue of pricing decisions of REITs based on reciprocal preferences and evolutionary game theory. It is found that when the proportion of REITs issuers choosing to construct a reciprocal initial pricing decision is greater than the equilibrium probability of REITs issuers choosing a reciprocal pricing strategy, and when the initial proportion of investors choosing a reciprocal investment decision is greater than the equilibrium probability of investors choosing a reciprocal investment strategy, the overall REITs transaction market tends to be a reciprocal and harmonious transaction market at this time, the overall happiness of the REITs trading market is the highest, and the success rate of trading increases and the capital circulation of the real estate market is accelerated. Therefore, it is recommended that issuers choose reciprocal competitive decisions when pricing REITs in order to increase the success rate of their own REIT holdings; and it is recommended that the government, when regulating the pricing of REITs, pays attention to the psychological factors of reciprocal preferences of issuers and investors and that the government penalizes REIT issuers and investors when they choose self-serving decisions and rewards them when they choose reciprocal decisions.

The pseudo-information entropy of Z-number and its applications in multi-attribute decision-making

In order to find a reasonable and effective approach to describe the information contained in a specific Z-number, we introduce information entropy into Z-number environment in this paper, and investigate its applications in multi-attribute decision-making (MADM) issues. Moreover, aiming at the problem with the weighting indicated by Z-number values, we propose two novel weighting methodologies based on conditional entropy and sigmoid function, respectively. Firstly, on the basis of the maximum entropy principle, the optimization model to calculate the underlying probability distribution of Z-number is introduced. And then, we define Z-number pseudo-information entropy, and a novel Z-VIKOR method is proposed to solve a selecting regional circular economy development plan issue from the perspective of information entropy. Furthermore, we propose Z-number pseudo-conditional entropy, and the relationship between Z-number pseudo-information entropy and Z-number pseudo-conditional entropy is investigated. Subsequently, a weighting method based on information entropy of Z-number is proposed. In addition, we also introduce the weighting approach based on the sigmoid function decision-making method. Finally, we introduce a government new energy investment problem to verify and compare the effectiveness of the new weighting approaches. The new method gives a solution to the problem related to Z-number from the perspective of information entropy.

An Interactive Weighted Geometric Aggregation Operator on T2IFS

Type 2 intuitionistic fuzzy sets (T2IFS) appear to be an attractive and potentially useful tool for coping with uncertainty and inaccurate data in today’s uncertain and ambiguous world. Consequently, it is frequently employed in decision-making (DM) issues. In the DM procedure, it is essential to aggregate the information provided by the experts. The Aggregation operators (AOs) are effective information combining tools. Therefore, this study aims on developing geometric and interactive geometric AOs on T2IFSs. To demonstrate the efficacy of the proposed operator, the optimal e-learning tool selection MCDM problem is solved. The results demonstrate that the proposed interactive AO outperforms existing arithmetic AOs and is applicable to all DM problems.

The Connotation Evolution and Enhancement Strategies of Digital Leadership in China's Universities in the Context of Digital Transformation

Global digital transformation is affecting all walks of life in a subtle way, and higher education is among them. Digitalization has undoubtedly become one of the core issues in school governance decision-making, and the digital leadership of college leaders is the key to promote the digital transformation of school education to adapt to the digital wave. However, considering the theoretical level, practical level and individual level, it is found that the level of digital leadership of university leaders is weak and urgent changes need to be made. Based on the evolution of the connotation of the dual theories of informatization leadership and digital leadership, the study traces the origins of digital leadership at home and abroad through the literature research method, and combs through the essential differences between educational informatization leadership and digital leadership from four aspects: leadership concept, application scope, data value, and competence requirements, so as to put forward the strategy of improving digital leadership for college leaders: The first is to transform the cognition of digital technology and improve the inductive reflection power of digital application; the second is to strengthen the cultivation of digital planning power and formulate the standard of digital leadership; the third is to cultivate the power of data decision-making and analysis, and to call for the formation of school data team. In order to provide certain reference for the reform and construction of digital team of leaders in China's colleges and universities in the new era.