Determine Weights Of Criteria Research Articles

Determining criteria weights for vehicle tracking system selection using PIPRECIA-S

Vehicle tracking systems are generally used to determine the location of vehicles, monitor them, and guide them when appropriate. This study aims to define the criteria that logistics companies consider when selecting a vehicle tracking system, as well as the relative importance of these criteria. PIPRECIA-S, a multi-criteria decision analysis method, was used in this context. According to the analysis results, the most important criterion in the selection of a vehicle tracking system is real-time tracking of the vehicle's location. When it comes to selecting a vehicle tracking system, logistics firms should prioritize instant vehicle tracking, compliance with local rules, compatibility with new technologies and software, quality certification, and compatibility with external systems-devices over other criteria. Other important criteria to consider when selecting a vehicle tracking system are system maintenance and technical support, providing statistical data collection and effective reporting, allowing the vehicle to be diverted, comprehension, simplicity of implementation and visual geo-information presentation for users, design and quality of hardware, system cost, communication infrastructure, and reducing the operating costs of companies. Also, when developing vehicle tracking systems, system developers can prioritize the aforementioned criteria.

T-Spherical Fuzzy Frank Aggregation Operators and Their Application to Decision Making With Unknown Weight Information

The current study presents a novel multi-criteria decision making (MCDM) approach to address decision analysis with T-spherical fuzzy data, whose weights of criteria are fully unknown. To serve the purpose, we design some generalized operational laws, namely Frank operational laws for T-spherical fuzzy numbers (T-SFNs) using Frank t-norm and t-conorm. Then, based on the proposed operations, a range of T-spherical fuzzy aggregation operators is developed to aggregate T-spherical fuzzy information efficiently. Also, discuss their particular cases and desirable properties are well proved. Next, we propound the T-spherical fuzzy entropy measure and its capability to fulfil the required properties. Then it is further used for criteria weight determination in the proposed aggregation based MCDM approach. In addition, a descriptive example is provided for viewing the applicability of the established approach. Lastly, the superiority and validity of this approach are highlighted by parameter analysis and comparative analysis.

Determining The Weights of Biophilic Design Parameters via SWARA Method

This study is conducted to determine the weights of biophilic design parameters created by empirical experiments in the literature and the effects of the human-space-nature relationship in human psychology, due to the recent COVID-19 pandemic that the whole world has been exposed to. It is aimed to calculate the weights of biophilic design parameters, that are discussed under 3 main headings and 14 basic parameters in the literature by using the SWARA method, which is used to determine criteria weights in decision making and performance evaluation processes. Accordingly, a survey has been conducted on 40 national and international architects working for both academic and non-academic environments. The survey results are used in the SWARA method and the weights of the biophilic design parameters are determined. According to the results obtained, prospect (wide panorama), visual connection with the nature and connection with the natural system parameters and processes are determined as the most important design parameters to determine the effects of human-space-nature relationship in human psychology. It is also aimed to use these results in further studies to establish and to develop the concepts like "Biophilic Footprint" or "Biophilic Efficiency Coefficient" in the architectural literature.

A hybrid fuzzy decision making approach for sitting a solid waste energy production plant

The rapid and uncontrolled growth of the world's population technological developments, increase in the social welfare and the transformation of societies into consumer societies have changed the dimensions of environmental problems. Nowadays waste management has become an important issue for the solution of environmental problems. Hence, we discussed the municipal solid waste management. Municipal solid waste management problem is a complex and it has many different aspects as political, social, technological and economical criteria have to consider. The evaluation of these criteria numerically is complicated and vague. This paper deals with this complexity by proposed methodology. Also the contribution of the article to the literature is that the proposed methodology is applied for the first time in municipal solid waste management problems. In this paper, two fuzzy decision making approaches are combined for sitting a waste to energy plant in the Kırıkkale in Turkey. Four alternative locations and nine criteria are defined from the expert opinions and the literature survey. A new hybrid methodology that has not been applied before for this decision problem is proposed. In proposed methodology, there are two main stages. Criteria weights determination is the first stage, and ranking of the alternative locations is the second stage of the methodology. In first stage, Interval type 2 Fuzzy Analytic Hierarchy process method is performed and in the second stage hesitant fuzzy technique for order preference by similarity to an ideal solution method is used for ranking the alternative locations. Also decision makers have different experience level and knowledge about the problem and different decision makers’ weights are considered for group decision making. Two fuzzy methods are combined for the solid waste energy production plant location selection problem. As a result of the study, the second alternative (Bahsılı-Bedesten) is determined as the most suitable area for waste to energy production plant. Besides, with scenario analysis the effect of criteria on ranking of the alternatives is analyzed.

A NOVEL PERFORMANCE EVALUATION FRAMEWORK FOR NEW SERVICE DEVELOPMENT IN THE HEALTHCARE INDUSTRY USING HYBRID ISM AND ANP

Today, the innovative activities of companies in new service development (NSD) have an undeniable contribution to the economic development of countries. Given the recent advances in the healthcare industry, the issue of NSD and performance management of firms operating in this industry has received special attention of researchers and decision makers. A review of previous research shows that on the one hand there is no agreement among experts on NSD performance measurement criteria and on the other hand there has been no systematic framework that can measure and manage firm performance in this area. The proposed framework should allow for interaction between different decision makers, considering multiple and sometimes conflicting criteria. In this regard, this paper aimed to provide a framework to assess the NSD performance in healthcare industry using multiple-criteria-decision-making methods. The proposed model consists of 17 different criteria that have been identified and finalized based on previous studies as well as experts’ opinions. Then, the indicators are classified with the help of experts in the form of a balanced scorecard model and presented as an initial model. Due to internal relationships between criteria, this model was evaluated using interpretive structural modelling and modelled at 5 different levels. Then, the analytic network process approach was applied to determine criteria weights. Finally, new service development performance in Moheb hospital was evaluated through the framework proposed here.

Redefined fuzzy rough set models in fuzzy β-covering group approximation spaces

The research purpose of this paper is to explore some new fuzzy rough set models in the fuzzy β-covering group approximation space (FβCGAS) and study the related properties, thereby provide new thinking directions for the theoretical development and application expansion of fuzzy rough set models. Firstly, in the fuzzy β-covering approximation space (FβCAS), in light of some existing fuzzy covering rough set (FCRS) models which do not satisfy the inclusion relations between the fuzzy upper and lower approximations, we define the concepts of parameterized fuzzy β-neighborhoods and parameterized fuzzy complementary β-neighborhoods to eliminate part of the noise data and establish four types of parameterized FCRS models that satisfy the inclusion relationship between the fuzzy lower and upper approximations. Meanwhile, the properties of the models are discussed. Further, in the FβCGAS, we define the concepts of the parameterized pessimistic (optimistic) fuzzy β-fitting neighborhoods and the parameterized pessimistic (optimistic) fuzzy complementary β-fitting neighborhoods and construct the parameterized pessimistic and optimistic FCRS models that satisfy the inclusion relationship between the fuzzy lower and upper approximations. At the same time, we likewise explore the properties of the models. Besides, we further use the newly proposed parameterized fuzzy neighborhoods to study the variable precision multi-granulation fuzzy decision-theoretic rough set models in the FβCGAS. Finally, for all the models mentioned above, we recommend them for solving the criteria weight determination problem, ranking problem, optimal selection problem and qualitative classification problem in multi-criteria decision-making. Meanwhile, we complete the relationships of all the new models mentioned in this paper and discuss them.

An Extended LBWA Framework in Picture Fuzzy Environment Using Actual Score Measures Application in Social Enterprise Systems

Level-based weight assessment (LBWA) model is a recently introduced algorithm for determining criteria weights for multi-criteria group decision making. In this paper, the authors aim to extend the basic framework of LBWA in the picture fuzzy (PF) environment using actual score (AS) measures of the picture fuzzy numbers (PFN). They apply this extended framework in addressing a real-life problem pertaining to social entrepreneurship or social entrepreneurs (SE) in the context of COVID-19. They endeavor to identify the critical challenging factors of SE in the new normal. They list the challenges as revealed through literature review and take the opinion of a group of SEs using PF linguistic scale. They then apply the proposed framework, actual score-based picture fuzzy LBWA. They notice that ability to withstand disruption risk and show resilience and fund availability and creation of a supporting business ecosystems are the major challenges that SEs face in the new normal. They carry out validity checking and sensitivity analysis, which show reasonable consistency and stability in the result.

Comparative Analysis of Solar Panels with Determination of Local Significance Levels of Criteria Using the MCDM Methods Resistant to the Rank Reversal Phenomenon

This paper aims to present an innovative approach based on two newly developed Multi-Criteria Decision-Making (MCDM) methods: COMET combined with TOPSIS and SPOTIS, which could be the basis for a decision support system (DSS) in the problem of selecting solar panels. Solar energy is one of the most promising and environmentally friendly energy sources because of the enormous potential of directly converting available solar radiation everywhere into electricity. Furthermore, ever-lower prices for photovoltaic systems make solar electricity more competitive with power from conventional energy sources, increasing interest in solar panels among companies and households. This fact generates the need for a user-friendly, objective, fully automated DSS to support the multi-criteria selection of solar panels. Both MCDM methods chosen for this purpose are rank-reversal-free and precise. First, the objective entropy weighting method was applied for determining criteria weights. Final rankings were compared by two ranking correlation coefficients: symmetrical rw and asymmetrical WS. Then the sensitivity analysis providing local weights of alternatives for decision criteria was performed. The obtained results prove the adequacy and practical usefulness of the presented approach in solving the problem of solar panels selection.

Arahan Pengembangan Hutan Rakyat untuk Penanganan Lahan Kritis di Kabupaten Sukabumi, Provinsi Jawa Barat

Community forest plants can be an alternative fulfillment of raw material for the timber industry. While Sukabumi Regency is region with the largest area in West Java Province, so it the potential for development of community forest plants. This study wants to find the availability of land for development community forest plants, analyzing the suitability of community forest plantations, and formulating direction for development community forest plants in Sukabumi Regency. The study was conducted in Sukabumi Regency, which began in February-August 2019. The data used is the weight of each criteria for suitability of community forest plants from experts, data Land Map Units from BBSDLP, land use maps, RTRW maps, forest area maps, and land licensing. The method used is spatial analysis for determining available land, Analytical Hierarchy Process (AHP) for determining criteria weights, Multi Criteria Evaluation (MCE) for analyzing land suitability, and spatial analysis for determining development priority directions. The results showed that availability land for development of community forest plants in Sukabumi Regency was 57,786 hectares. The available land area in Sukabumi Regency which is classified as suitable (S1, S2, S3) i.e 57%. The development of community forest plants is directed at priority 1, which is an 83%.

Research on teaching quality evaluation of college english based on the CODAS method under interval-valued intuitionistic fuzzy information

With the rapid development of China’s economic globalization in the new era, the demand for English majors is obviously on the rise, which puts forward new and higher requirements for application-oriented undergraduate colleges to train compound English majors. However, from the perspective of teaching quality evaluation of English majors in application-oriented undergraduate colleges, the results are not optimistic. Therefore, it is an important task for higher education research in China to explore the problems existing in the process of teaching quality evaluation for English majors in application-oriented undergraduate colleges and how to better train qualified and versatile talents for English majors to adapt to the economic and social development in the new era. The teaching quality evaluation of college English is frequently viewed as a multi-attribute group decision-making (MAGDM). Thus, a novel MAGDM method is used to tackle it. Depending on the conventional CODAS method and interval-valued intuitionistic fuzzy sets (IVIFSs), this paper designs a novel distance based IVIF-CODAS method to assess the teaching quality evaluation of college English. First of all, a related literature review is conducted. What’s more, some necessary theories related to IVIFSs are briefly reviewed. In addition, since subjective randomness frequently exists in determining criteria weights, the weights of criteria is decided objectively by utilizing CRITIC method. Afterwards, relying on novel distance measures between IVIFSs, the conventional CODAS method is extended to the IVIFSs to calculate assessment score of every alternative. Therefore, all alternatives can be ranked and the one with the best teaching quality. Eventually, an application about teaching quality evaluation of college English and some comparative methods have been employed to show the superiority of the developed method. The results illustrate that the defined framework is very useful for assessing the teaching quality of college English.

Hydrometeorological - Hydrometric Station Network Design Using Multicriteria Decision Analysis and GIS Techniques

The design of an optimum hydrometeorological and hydrometric station network constitutes a key factor for the collection of comprehensive and reliable hydrometeorological and flow data that are necessary both for decision making in water resources policy and management, and for the hydrometeorological risk assessment. This article describes a methodology developed in a geographic information system (GIS) using a multicriteria decision making (MCDM) approach, which combines several spatial criteria to propose suitable locations for installation of such a station network in the Sarantapotamos River Basin in the western part of the Attica Region, Greece. Through the design of two networks that meet different requirements, various aspects concerning this methodology are illustrated, such as criteria weights determination, which is a problem that arises frequently in many MCDM techniques. The criteria weights for the hydrometric station network design are estimated using both the Analytic Hierarchy Process (AHP) and the Fuzzy Analytic Hierarchy Process (FAHP), while, for hydrometeorological station network design, all weights are equal. Hydrometeorological station final position selection is achieved by introducing the criteria of density and spatial distribution to the suitable locations. For hydrometric station network design, the analysis indicates that the criterion of slope mainly controls the MCDM outputs. According to station density thresholds proposed by the World Meteorological Organization (WMO), an optimum hydrometeorological and hydrometric station network for the region should comprise three and two stations, respectively.

GRA and CRITIC Method for Intuitionistic Fuzzy Multiattribute Group Decision Making and Application to Development Potentiality Evaluation of Cultural and Creative Garden

In recent years, cultural and creative industry park is becoming a kind of hot industry to promote industrial restructuring and to improve the quality of urban space. For this reason, cultural and creative industrial parks are planning to build across the country. Currently, cultural and creative industrial parks that develop better than others thank to the government’s overall planning, construction, marketing, and management. At the same time, the new cultural and creative industry parks face enormous challenges, such as how to have together the cultural and creative industries and related groups or how to have area cultural creativity. And it is frequently regarded as a multiattribute group decision-making (MAGDM) process. Thus, a novel MAGDM process is needed to tackle it. Depending on the conventional grey relational analysis (GRA) method and intuitionistic fuzzy sets (IFSs), this paper designs a novel intuitive distance-based IF-GRA method for development potentiality evaluation of cultural and creative garden. First of all, some necessary theories related to IFSs are briefly reviewed. In addition, since subjective randomness frequently exists in determining criteria weights, the weights of criteria are decided objectively by utilizing the CRITIC method. Afterwards, relying on novel distance measures between IFSs, the GRA method is extended to the IFSs to calculate assessment score of each alternative. Eventually, an application about development potentiality evaluation of cultural and creative garden and some comparative analysis is given. The results think that the designed method is useful for development potentiality evaluation of cultural and creative garden.

Fuzzy AHP – DEMATEL Methods To Investigate Passengers’ Decision Factors On Using Public City Bus In An Indonesian Region

An advanced public transportation system becomes an indicator for a country. Accordingly, it is essential that the decision-makers (DMs) conduct an initial study based on passengers’ view in order to improve the public transportation services. Since involving multi factors, the problem is often solved using the multi-criteria decision-making (MCDM) approaches. This study aims to examine significant factors on passengers decision making to use public transportation using Fuzzy AHP and DEMATEL. The Fuzzy AHP method is proposed to determine criteria weights so that significant critera are obtained, then the causal relations including the criteria are visualized using DEMATEL. This study demonstrates the integration of the two MCDM methods in a BRT system in the region of Yogyakarta, Indonesia, and invites passengers and the DMs. The result indicated that 21 criteria are identified, while the 11 significant criteria are selected based on the Fuzzy AHP weight – α-cut screening. Besides, the DEMATEL has succeeded in describing the influence relationship for the criteria, where firstly, the significant criteria are classified into cause and effect group and secondly, the two criteria, namely coverage to strategic points and on time arrival, should be put on the top priority list. This study enables the DMs to solve public transportation problems more effectively. However, the follow-up study should be carried out by including other factors such as economic and sustainability to strengthen the decision-making process.

Coupling Fuzzy Multi-Criteria Decision-Making and Clustering Algorithm for MSW Landfill Site Selection (Case Study: Lanzhou, China)

The siting of Municipal Solid Waste (MSW) landfills is a complex decision process. Existing siting methods utilize expert scores to determine criteria weights, however, they ignore the uncertainty of data and criterion weights and the efficacy of results. In this study, a coupled fuzzy Multi-Criteria Decision-Making (MCDM) approach was employed to site landfills in Lanzhou, a semi-arid valley basin city in China, to enhance the spatial decision-making process. Primarily, 21 criteria were identified in five groups through the Delphi method at 30 m resolution, then criteria weights were obtained by DEMATEL and ANP, and the optimal fuzzy membership function was determined for each evaluation criterion. Combined with GIS spatial analysis and the clustering algorithm, candidate sites that satisfied the landfill conditions were identified, and the spatial distribution characteristics were analyzed. These sites were subsequently ranked utilizing the MOORA, WASPAS, COPRAS, and TOPSIS methods to verify the reliability of the results by conducting sensitivity analysis. This study is different from the previous research that applied the MCDM approach in that fuzzy MCDM for weighting criteria is more reliable compared to the other common methods.

IF-MABAC Method for Evaluating the Intelligent Transportation System with Intuitionistic Fuzzy Information

Intelligent transportation system (ITS) is the development direction of the future traffic system. ITS can effectively employ the existing traffic facilities and ensure the safety of traffic, urban traffic, and public security management for effective control in order to satisfy people’s travel demand. Therefore, the results of the system in-depth understanding and objective evaluation are very necessary. And it is frequently regarded as a multiattribute group decision-making (MAGDM) issue. Thus, a novel MAGDM method is required to tackle it. Depending on the conventional multiattributive border approximation area comparison (MABAC) method and intuitionistic fuzzy sets (IFSs), this article designs a novel intuitive distance-based IF-MABAC method to assess the performance of financial management. First of all, a related literature review is conducted. Furthermore, some necessary theories related to IFSs are briefly reviewed. In addition, since subjective randomness frequently exists in determining criteria weights, the weights of criteria are decided objectively by utilizing the maximizing deviation method. Afterwards, relying on novel distance measures between intuitionistic fuzzy numbers (IFNs), the conventional MABAC method is extended to the IFSs to calculate the final value of each enterprise. Therefore, all enterprises can be ranked, and the one with the best environmental behaviors and awareness can be identified. Eventually, an application for evaluating the intelligent transportation system and some comparative analyses have been given. The results illustrate that the designed algorithm is useful for assessing the performance of financial management.

Determination of Objective Weights Using a New Method Based on the Removal Effects of Criteria (MEREC)

The weights of criteria in multi-criteria decision-making (MCDM) problems are essential elements that can significantly affect the results. Accordingly, researchers developed and presented several methods to determine criteria weights. Weighting methods could be objective, subjective, and integrated. This study introduces a new method, called MEREC (MEthod based on the Removal Effects of Criteria), to determine criteria’ objective weights. This method uses a novel idea for weighting criteria. After systematically introducing the method, we present some computational analyses to confirm the efficiency of the MEREC. Firstly, an illustrative example demonstrates the procedure of the MEREC for calculation of the weights of criteria. Secondly, a comparative analysis is presented through an example for validation of the introduced method’s results. Additionally, we perform a simulation-based analysis to verify the reliability of MEREC and the stability of its results. The data of the MCDM problems generated for making this analysis follow a prevalent symmetric distribution (normal distribution). We compare the results of the MEREC with some other objective weighting methods in this analysis, and the analysis of means (ANOM) for variances shows the stability of its results. The conducted analyses demonstrate that the MEREC is efficient to determine objective weights of criteria.

Distance measures on intuitionistic hesitant fuzzy set and its application in decision-making

Intuitionistic hesitant fuzzy set (IHFS) provides a valid mean for dealing with the uncertainty of complex problems. Information measures on IHFS can measure the uncertain information, so that we shall introduce a method to construct a class of distance measures for IHFS in this paper. For constructing more objective distance measures to reflect the actual situation, we consider the information content and information clarity of IHFS simultaneously and utilize different functions to adjust their contribution. Its superiority is evidenced by an example of pattern recognition that the proposed distance measure improves numerically results obtained with existing distance measures. In particular, we investigate the connection between distance measure, similarity measure, and entropy measure of IHFS, and prove that they can be constructed mutually under this axiomatic framework. On this basis, we apply the proposed entropy measure to determine criteria weights in multi-criteria decision-making problems and design an extended intuitionistic hesitant fuzzy technique for order preference by similarity to an ideal solution (TOPSIS) method, which effectiveness is presented by a practical application.

Group decision-making framework for site selection of coastal nuclear power plants in a linguistic environment: a sustainability perspective

ABSTRACT Site selection of nuclear power plants (NPPs) is a critical task since it has a significant influence on individual safety, environmental protection, and regional development. The objective of this study is to develop a multi-criteria group decision-making (MCGDM) framework in a linguistic environment that allows the government or the developer to select the optimal site for a costal NPP. This framework is composed of three primary parts: establishment of ranking criteria from a perspective of sustainability, determination of criteria weights using an entropy weight model, and aggregation of decision information by two compromise programing methods to compare and rank preferred candidate sites for NPPs. Finally, a case study in Fujian province, China is provided to demonstrate the applicability of the framework. The results show that there are significant differences between the weight values of criteria by level. The proposed approach is effective for selection of the most appropriate coastal NPP in consideration of sustainability under linguistic environments since the selected site is consistent with the feasibility report of NPP selection from the government. The findings provide a theoretical reference for NPP site selection involving multiple criteria and a small scale of decision makers and are also beneficial for sustainable nuclear power development and future energy structure optimization.

A spherical fuzzy methodology integrating maximizing deviation and TOPSIS methods

Due to the uncertainty and vagueness, ambiguity and subjectivity of the information in an intricate decision-making environment, the assessment data specified by experts are mostly fuzzy and uncertain. As an extension of Pythagorean fuzzy sets (PyFSs) and picture fuzzy sets (PFSs), spherical fuzzy sets (SFSs) are used frequently for presenting fuzzy and indeterminate information. In multi-criteria decision-making (MCDM) problems, the weights of criteria are not known generally. The maximizing deviation technique is a useful tool to handle such problems that we have partially or incomplete information about the criteria’ weights. This research expands the classical maximizing deviation technique to the spherical fuzzy maximizing deviation technique using single-valued (SV) and interval-valued (IV) spherical fuzzy sets to determine criteria weights. To rank the alternatives and specify the preeminent preference, we proposed the Interval Valued Spherical Fuzzy TOPSIS method based on the similarity measure instead of distance measure. For this purpose, we proposed an IVSF cosine similarity measure. To present its effectiveness and practicability, we apply the proposed methodology to an advertisement strategy selection problem, where IVSF sets are used to represent the evaluations about alternatives and criteria. A sensitivity analysis with different similarity measurements is performed to show the reliability of the proposed methodology.

Application of multi-attribute group decision-making methods in urban road traffic safety evaluation with interval-valued intuitionistic fuzzy information

With the development of the social economy, the level of motorization has been greatly improved, and the traffic safety problem has been paid more and more attention. In recent years, China’s road traffic accident rate showed a trend of decline after rising first, suggests that the Chinese road traffic safety level is on the decline. Road traffic safety evaluation has a positive effect in found risk factors of road traffic safety in time and reduce the traffic accident rate, so the study of traffic safety evaluation method is imperative. And the urban road traffic safety evaluation is frequently viewed as the multi-attribute group decision-making (MAGDM) problem. Depending on the conventional VIKOR method and interval-valued intuitionistic fuzzy sets (IVIFSs), this paper designs a novel IVIF-VIKOR method to assess the urban road traffic safety. In addition, since subjective randomness frequently exists in determining criteria weights, the weights of criteria is [Z1] decided objectively by utilizing CRITIC method. Eventually, an application and some comparative analysis are given. The results show that the designed algorithms are useful for assessing the urban road traffic safety.