Negative Ideal Point Research Articles

Optimization of Emergency Alternatives for Hydrogen Leakage and Explosion Accidents Based on Improved VIKOR

Hydrogen leakage and explosion accidents have obvious dangers, ambiguity of accident information, and urgency of decision-making time. These characteristics bring challenges to the optimization of emergency alternatives for such accidents. Effective emergency decision making is crucial to mitigating the consequences of accidents and minimizing losses and can provide a vital reference for emergency management in the field of hydrogen energy. An improved VIKOR emergency alternatives optimization method is proposed based on the combination of hesitant triangular fuzzy set (HTFS) and the cumulative prospect theory (CPT), termed the HTFS-CPT-VIKOR method. This method adopts the hesitant triangular fuzzy number to represent the decision information on the alternatives under the influence of multi-attributes, constructs alternatives evaluation indicators, and solves the indicator weights by using the deviation method. Based on CPT, positive and negative ideal points were used as reference points to construct the prospect matrix, which then utilized the VIKOR method to optimize the emergency alternatives for hydrogen leakage and explosion accidents. Taking an accident at a hydrogen refueling station as an example, the effectiveness and rationality of the HTFS-CPT-VIKOR method were verified by comparing with the existing three methods and conducting parameter sensitivity analysis. Research results show that the HTFS-CPT-VIKOR method effectively captures the limited psychological behavior characteristics of decision makers and enhances their ability to identify, filter, and judge ambiguous information, making the decision-making alternatives more in line with the actual environment, which provided strong support for the optimization of emergency alternatives for hydrogen leakage and explosion accidents.

A Monotonous Intuitionistic Fuzzy TOPSIS Method Under General Linear Orders via Admissible Distance Measures

All intuitionistic fuzzy TOPSIS methods contain two key elements: (1) the order structure, which can affect the choices of positive ideal-points and negative ideal-points, and construction of admissible distance/similarity measures; (2) the distance/similarity measure, which is closely related to the values of the relative closeness degrees and determines the accuracy and rationality of decision-making. For the order structure, many efforts are devoted to constructing some score functions, which can strictly distinguish different intuitionistic fuzzy values (IFVs) and preserve the natural partial order for IFVs.This paper proves that such a score function does not exist, namely the application of a single monotonous and continuous function does not distinguish all IFVs. For the distance or similarity measure, some examples are given to show that classical similarity measures based on the normalized Euclidean distance and normalized Minkowski distance do not meet the axiomatic definition of intuitionistic fuzzy similarity measures. Moreover,some illustrative examples are given to show that classical intuitionistic fuzzy TOPSIS methods do not ensure the monotonicity with the natural partial order or linear orders, which may yield some counter-intuitive results. To overcome the limitation of non-monotonicity, we propose a novel intuitionistic fuzzy TOPSIS method,using three new admissible distances with the linear orders measured by a score degree/similarity function and accuracy degree, or two aggregation functions, and prove that the proposed TOPSIS method is monotonous under these three linear orders.} This is the first result with a strict mathematical proof on the monotonicity with the linear orders for the intuitionistic fuzzy TOPSIS method.

Research on Multiple Affective Responses Design of Product Based on Kansei Engineering and TOPSIS-AISM

Affective response reflects the user’s emotional needs, and capturing affective response is very important for a product. But consumers’ emotional needs are complex, and a product design system based on a single affective response (SAR) of consumers cannot produce an appropriate design scheme when considering affective responses (MARs). This study proposes a MARs product appearance design method based on KE-TOPSIS-AISM to explore the transformation between MARs and appearance design. First, Kansei Engineering (KE) is used to get consumer perceptual adjectives and a product sample database. Second, the product design elements and market styles were compared in partial order using the TOPSIS of positive and negative ideal point distance and close degree, and the pros and cons ranking was obtained. Meanwhile, the AISM is used to create topological hierarchy diagrams. Finally, a project verifies the practicality of the method, providing a novel notion for MARs product appearance design study.

Supplier selection in sustainable supply chains: Using the integrated BWM, fuzzy Shannon entropy, and fuzzy MULTIMOORA methods

With the increasing awareness of environmental protection and social responsibility, sustainable supplier selection (SSS) has been receiving more and more attention. However, traditional methods for selecting sustainable suppliers suffer from three main drawbacks: (i) Few existing studies have considered criteria weightings that have been determined both subjectively and objectively, reasonably and simultaneously. Moreover, among these limited studies, existing methods for combining weightings that have been calculated both subjectively and objectively provide only a poor degree of differentiation. (ii) Although MULTIMOORA method has high potential to solve the complex SSS problem, few researchers have given it much attention. (iii) The current Reference Point Approach within MULTIMOORA is not comprehensive as it only considers the distance between the alternative and the positive ideal point. Together, these drawbacks result in both inefficiency and ineffectiveness in SSS. This paper proposes a novel fuzzy MULTIMOORA-based method for SSS. The proposed method, firstly, obtains weights by both group Best Worst Method (subjective method) and fuzzy Shannon Entropy Method (objective method), respectively. Then the two types of weights are combined by Deviation Maximization method, reasonably and effectively. Finally, the paper introduces an improved fuzzy MULTIMOORA method to rank alternative suppliers, which considers both the minimum distance from the positive ideal point and the maximum distance from the negative ideal point. The practicability and effectiveness of the proposed method is verified in an illustrative application in Company L, a well-known international forklift truck manufacturer in China.

Assessment of International Competitiveness of AI Industry Based on Positive and Negative Ideal Points Weighting Method

China, the United States, the United Kingdom, Germany, and other major AI superpowers as research objects, this paper establishes the assessment index system with the diamond model, weights the international competitiveness indexes of AI industry in the four countries based on positive and negative ideal points, and applies the simulated annealing (SA) algorithm to obtain the final weights. Then, the TOPSIS assessment method is used to score and rank their international competitiveness of AI industry. It is concluded that the United States is on the leading position in the human factor, knowledge factor, capital factor, enterprise strategy structure/competitors, and policy laws and regulations. China has a complete infrastructure system and huge market demand. The leading of these indicators is also the reason why China can catch up in the development of some industries when it participates in the global value division. Europe also performs well in knowledge factors, capital factors, strategic structure/competitors, and policies and regulations but needs to invest more in AI industry infrastructure. Finally, this paper analyzes the advantages and disadvantages of the countries and reasons to provide comparative reference among different countries for AI industry.

EVALUATION OF THE BUSINESS ENVIRONMENT OF PARTICIPATING COUNTRIES OF THE BELT AND ROAD INITIATIVE

As an important indicator for measuring the quality of business environment of different countries, ease of doing business (EDB) issued by the World Bank (WB) provides an important reference for investors in making decisions on transnational investment. The calculation method for EDB issued by the WB is improved using a technique for order preference by similarity to an ideal solution (TOPSIS) method based on Mahalanobis distance. Based on various indicator data in 2019, business environments in 121 countries participating in “the Belt and Road Initiative (BRI)” were empirically analysed and compared through such models. The result showed that TOPSIS method based on Mahalanobis distance can more fully utilise information and take the effect of negative ideal points into account. Therefore, compared with ranking method by the WB, TOPSIS method based on Mahalanobis distance is more applicable for ranking BRI countries. The ranking results indicated significant geographical characteristics. The EDB rankings obtained through the WB overestimate the business environments of countries in Central and Eastern Europe while underestimate those in Southeast Asia, Africa, etc.

A Multi-Attribute Pearson’s Picture Fuzzy Correlation-Based Decision-Making Method

As a generalization of several fuzzy tools, picture fuzzy sets (PFSs) hold a special ability to perfectly portray inherent uncertain and vague decision preferences. The intention of this paper is to present a Pearson’s picture fuzzy correlation-based model for multi-attribute decision-making (MADM) analysis. To this end, we develop a new correlation coefficient for picture fuzzy sets, based on which a Pearson’s picture fuzzy closeness index is introduced to simultaneously calculate the relative proximity to the positive ideal point and the relative distance from the negative ideal point. On the basis of the presented concepts, a Pearson’s correlation-based model is further presented to address picture fuzzy MADM problems. Finally, an illustrative example is provided to examine the usefulness and feasibility of the proposed methodology.

Novel ranking method for intuitionistic fuzzy values based on information fusion

In this paper, a novel ranking method for intuitionistic fuzzy values is proposed and applied to multi-attribute decision making problems. At first, a new intuitionistic fuzzy entropy (IFE) is designed to fully express the two facets of uncertainty expressed by intuitionistic fuzzy sets (IFSs): the fuzziness and the unknown. Then, after considering the distance to the positive ideal point and the negative ideal point simultaneously, the closeness degree of technique for order preference by similarity to ideal solution (TOPSIS) is used to characterize the amount of information conveyed by IFSs. The closeness degree is merged with the designed IFE by DMs’ risk attitude, and a novel single-time ranking method is constructed. After that, by minimizing the distance to the objectivity and subjectivity simultaneously, the optimal attribute weights are derived by solving the optimization model. Furthermore, a normalized time sequence weight model is proposed to aggregate information from multiple time periods. Finally, a benchmark example is used to illustrate the flexibility and rationality of the proposed method.

GEOSPATIAL MULTI-CRITERIA DECISION BASED SITE SUITABILITY ANALYSIS FOR SOLID WASTE DISPOSAL USING TOPSIS ALGORITHM

Abstract. The problem of Urban Municipal solid waste disposal is a challenging task faced by civic bodies and planning authorities in almost all the cities of rapidly developing countries like India. A similar situation is being faced by Dehradun, the capital, and the fastest growing city of Uttarakhand, India. In the current study, an attempt has been made to find out the suitable sites for waste disposal in the area around Dehradun city using Geospatial Multi-criteria Decision Analysis (MCDA) techniques from remote sensing data. Two different decision rules of MCDA are used, namely, Analytical Hierarchical Process based Weighted Linear Combination (AHP – WLC) and Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS). WLC has been used previously for similar studies for its ease and simplicity to apply in raster format but TOPSIS has an advantage over WLC, it orders a set of alternatives on the basis of their separation from the ideal point. It defines the best alternative as the one that is simultaneously closest to the ideal alternative and farthest from the negative ideal point. Raster-based suitability analysis has been done and the results obtained by the two methods are compared. Identical results with minor differences identifying best suitable sites outside the eastern boundary of the city where the existing dumping site is located are obtained. Also, new potential sites are identified in the western part of the city which faces the problem of waste disposal more acutely because of expansion of the city in that direction.

An Interval-Valued Pythagorean Fuzzy Compromise Approach with Correlation-Based Closeness Indices for Multiple-Criteria Decision Analysis of Bridge Construction Methods

The purpose of this paper is to develop a novel compromise approach using correlation-based closeness indices for addressing multiple-criteria decision analysis (MCDA) problems of bridge construction methods under complex uncertainty based on interval-valued Pythagorean fuzzy (IVPF) sets. The assessment of bridge construction methods requires the consideration of multiple alternatives and conflicting tangible and intangible criteria in intricate and varied circumstances. The concept of IVPF sets is capable of handling imprecise and ambiguous information and managing complex uncertainty in real-world applications. Inspired by useful ideas concerning information energies, correlations, and correlation coefficients, this paper constructs new concepts of correlation-based closeness indices for IVPF characteristics and investigates their desirable properties. These indices can be utilized to achieve anchored judgments in decision-making processes and to reflect a certain balance between connections with positive and negative ideal points of reference. Moreover, these indices can fully consider the amount of information associated with higher degrees of uncertainty and effectively fuse imprecise and ambiguous evaluative ratings to construct a meaningful comparison approach. By using the correlation-based closeness index, this paper establishes effective algorithmic procedures of the proposed IVPF compromise approach for conducting multiple-criteria evaluation tasks within IVPF environments. The proposed methodology is implemented in a practical problem of selecting a suitable bridge construction method to demonstrate its feasibility and applicability. The practicality and effectiveness of the proposed methodology are verified through a comparative analysis with well-known compromise methods and other relevant nonstandard fuzzy models.

Decision Model of Aero-Engine Design Integration Platform Implementation Solution Selection Based on Number Interval Number with Priority Order

Considering the fuzzy factors in the aero-engine design integration platform implementation solution selection, using the prioritized interval number evaluation method, the implementation model of the aero-engine design integration platform implementation solution selection is established, and the priority relationship is calculated according to the relative distance between each attribute and the ideal point. Through the calculation of the relative distance between the interval value and the negative ideal point, the single evaluation value is obtained. Finally, the comparison result of the pre-selected scheme is obtained by analysing and solving the preferred model. The model comprehensively considers the determining factors in the optimization process and uncertain factors, clear logic, and the best results obtained are comprehensive and reasonable.

An uncertain pure linguistic approach on evaluation of enterprise integrity based on grey information

Purpose Currently, for the evaluation of enterprise credit, many specific values of indexes are difficult to obtain, so decision makers tend to give a form of uncertain linguistic variable. To solve this kind of problem, the purpose of this paper is to introduce an uncertain pure linguistic approach on evaluation of enterprise integrity based on grey information. Design/methodology/approach Initial uncertain linguistic variables given by experts are transferred into interval grey numbers, and their greyness of degree is computed. Then, the greyness of degree is applied to adjust the weights of experts. Moreover, the core of each interval grey number is calculated, and through giving the positive ideal point and negative ideal point, which are binary numbers, the comprehensive grey relational grade between the linguistic number and the two points is calculated, respectively, as well to get the ranking result of projects by considering both core and greyness of degree. Findings The model is applied to a case, and the result verifies the validity and practicability of the model which reveals high effectiveness. Practical implications This model provides a new feasible method in a growing number of fuzzy evaluation schemes in the fields of enterprise integrity and contributes to getting better and more accurate results. Originality/value In this paper, the greyness of degree is introduced to the model to adjust the experts’ weights, and it reflects the thought of “making full use of the information” in grey system theory and further enriches the system of grey decision-making theory as well as expanding its application scope.

An integrating OWA–TOPSIS framework in intuitionistic fuzzy settings for multiple attribute decision making

In this paper, we develop an integrating OWA–TOPSIS approach in intuitionistic fuzzy environment to tackle fuzzy multiple attribute decision making problems. The proposed intuitionistic fuzzy OWA–TOPSIS method provides a general framework of diverse fuzzy information aggregation process including different determination methods of extreme points. There are six different types of information aggregation (s–p–d type, p–s–d type, s–d–p type, p–d–s type, d–s–p type and d–p–s type) following the different sequences of source aggregation, preference aggregation. During the different aggregation scenarios, positive ideal points and negative ideal points are identified as a point, a vector or a matrix. A real application example is provided to demonstrate in detail the proposed approach. The comparative results in total 32 experiments show the rankings consistency and different levels of information loss in the six different aggregation types. On the whole, the ranks are most precise in d–s–p and d–p–s types, and more precise in s–p–d and p–s–d types than that in s–d–p and p–d–s types.

Comparing trapezoidal fuzzy numbers by using a hybrid technique on the base of the ideal points and the centroid point

Comparing fuzzy numbers is a key task in decision making. Although, up to now several techniques have been introduced for ordering fuzzy numbers, nearly all of these methods contain various defects. In this paper, we introduce a new approach for ranking generalized trapezoidal fuzzy numbers. The su ggested technique combines the trait of two ideas namely positive and negative ideal points as well as the centroid point. This method is logically easy and has very straightforward computation. The benefits of the proposed method are discussed through a number of comparative numerical cases.

Determining winner in multi-attribute procurement auction: A method based on technical and business experts' evaluation information

A method for solving the winner determination problem(WDP) in multi-attribute procurement auctions is proposed, based on technical and business experts’ evaluation information. Firstly,on the background of procurements in China, a multi-attribute procurement auction mechanism is presented, where technical and business experts participate in the bid evaluation. Then, the concept of TOPSIS is used to determine the positive and negative ideal points of the WDP according to bid prices, the technical and business experts’ evaluation information. Further, the closeness coefficient of each bidder(candidate supplier) is obtained by calculating the distances to the positive and negative ideal points. Thus,the winning supplier can be determined according to the closeness coefficients. Finally, a numerical example is used to illustrate the use of the proposed method.

Multi-Attribute Decision Making Method Based on the Satisfaction under Interval-Valued Intuitionistic Fuzzy Environment

In this paper, it discussed multi-attribute decision making (MADM) problems in which the information about attribute weights is incomplete and decision-making information is characterized by interval-valued intuitionistic fuzzy number (IVIFNs), decision-making method is proposed based on the satisfaction. First, we define positive and negative ideal point of the comprehensive attribute values and satisfaction function, and make use of satisfaction function to establish a multi-objective optimization model, apply this model to determine the attribute weight vector, calculate the comprehensive attribute values, rank the alternatives according to the score function and precise function of the comprehensive attribute values. Finally, the examples are given to show that the method is reasonable and effective.

Optimization of Maintenance Equipment Tool Types Based on Triangle Fuzzy Number

In the face of those cases which multi-type equipments are configured by organizational systems and types for maintenance support, some questions are indicated. For example, the functions of some equipment tools are repetitive and similar. The amount of types is large and so on. Those phenomena are bad to flexibility, support and preserving in army. The fuzzy theory and triangular fuzzy number are used in this paper. Colony benefit is obtained after positive and negative ideal point and grey correlation coefficients are confirmed. The similar maintenance equipment tools are selected further to integrate equipment tool types. The method followed subjective and impersonal illegibility and excerpted indexing system and weight values. It is validated to be feasible and effective.

Research on Multi-Criteria Decision Based on Bidirectional Grey Relation Projection Method

There are many comprehensive efficiency evaluation problems in socioeconomic system, which are also taken as grey multi-criteria decision problems. Based on grey system theory and vector projection theorem, the grey relation projection method combines module with angle cosine to fully reveal the close degree of multiple decision schemes and the ideal scheme. Grey relation projection method considers spatial influences of factor indexes and is applicable to the situation of small sample and discrete data. However, traditional grey relation projection method can not solve the problem of sorting schemes with the same projection. On account of TOPSIS method, this paper studies bidirectional grey relation multi-criteria decision method on the basis of positive and negative ideal points from the perspective of vector projection, and constructs a bidirectional grey relation projection close degree calculating model. Analysis on application example shows that the method put forward in this paper has preferable feasibility and rationality.

Group decision making process for RFID-based system selection using fuzzy TOPSIS approach

The purpose of this article is twofold: first to introduce a multi attribute decision making model for radio frequency identification system consisting of four main criteria and five alternatives, and second to develop and solve the proposed fuzzy TOPSIS problem. Author presented an effective fuzzy multi-criteria method based upon the fuzzy model and the concepts of positive ideal and negative ideal solution points for solving problems with a group of multi decision makers. The fuzzy sets concepts are used to evaluate the performance of alternatives and the importance of criteria. The TOPSIS model used in this article is able to grasp the ambiguity exists in the utilized information and the fuzziness appears in the human judgments and preferences. TOPSIS technique can easily produce satisfactory results, and hence stimulates creativity and the invention for developing new methods and alternative approaches. This article is a very useful source of information both for radio frequency identification and multi attribute decision making using fuzzy TOPSIS methodology

Performance Evaluation for Gas Production Units Based on ANP

In view of the existing situation of gas field development, one kind of method to evaluate the production performance of gas production units (GPUs) was presented in this paper. Among the commonly used indicators of gas field development, we select 11 indicators from the three aspects of production task, gas reservoir management, and production technology. According to the principle of analytic network process (ANP), this paper introduced one kind of new method to get the weights of indicators. By means of the method of TOPSIS, it is easy to obtain the rankings for all the GPUs through calculating the weighted Euclidean distance between each GPU and the positive or negative ideal point. This evaluation method could constantly improve the management level of gas production units and deepen the delicacy management of gas field development.