A New Coefficient of Rankings Similarity in Decision-Making Problems

Sałabun, Wojciech; Urbaniak, Karol

doi:10.1007/978-3-030-50417-5_47

Cited by 170 publications

(130 citation statements)

References 36 publications

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“…With the use of aggregation operators and other fuzzy techniques, it is possible to generate new scenarios based on the expertise and expectations of the decision makers. Additionally, the use of different coefficients to test the similarity between the rankings will be useful to compare rankings in decision-making fields [54]. Finally, these new techniques can be applied in different areas such as economics, finance, engineering, social science and other areas [55] where the idea and characteristics of fuzzy logic and fuzzy sets can be used [56,57].…”

Section: Resultsmentioning

confidence: 99%

Bonferroni Prioritized Aggregation Operators Applied to Government Transparency

Pérez-Arellano¹,

Blanco‐Mesa

León‐Castro

et al. 2020

Mathematics

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This article applies the Bonferroni prioritized induced heavy ordered weighted average (OWA) to analyze a series of data and focuses on the Bonferroni average and heavy induced prioritized aggregation operators. The objective of the present work is to present a new aggregation operator that combines the heavy induced prioritized Bonferroni and its formulations and represents the Bonferroni mean with variables that induce an order with vectors that are greater than one. This work develops some extensions using prioritization. The main advantage is that different types of information provided by a group of decision makers to compare real situations are included in this formulation. Finally, an example using the operators to calculate the transparency of the websites of the 32 states of Mexico was performed. The main idea was to visualize how the ranking can change depending on the importance of the five components of the methodology. The main results show that it is possible to detect some important changes depending on the operator and the experts considered.

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Section: Resultsmentioning

confidence: 99%

Bonferroni Prioritized Aggregation Operators Applied to Government Transparency

Pérez-Arellano¹,

Blanco‐Mesa

León‐Castro

et al. 2020

Mathematics

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show abstract

“…Although some barriers on using the fuzzy BWM are observed, the advantages on conducting a smaller number of pairwise comparisons outweigh the drawbacks. In addition, to compare them qualitatively, the evaluations of weighted spearman's rank correlation coefficient (r ω ) and rank similarity coefficient (WS) are conducted to examine the ranking performance between the fuzzy BWM and fuzzy AHP [31], as in Equations (14) and (15). R xi and R yi represent the expected and estimated ranking results at alternative i, respectively, while N denotes the total number of alternatives.…”

Section: Comparisons With Using Fuzzy Ahpmentioning

confidence: 99%

New Product Idea Selection in the Fuzzy Front End of Innovation: A Fuzzy Best-Worst Method and Group Decision-Making Process

Chan

Tsang

et al. 2021

Mathematics

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New product development (NPD) is essential to most business organizations to create new values and protect existing values for maintaining high profitability and sustainability. However, the success of NPD projects is deemed to be difficult and challenging owing to high organizational complexity, uncertain business environment, and time-critical innovation. Under the smart manufacturing paradigm, NPD is an active research area to establish effective measures through the adoption of systematic approaches so as to facilitate idea management in the fuzzy front end for the product innovation. In this paper, the domain of new product idea selection is focused on and enhanced by means of the multi-criteria decision-making (MCDM) approach, in which multiple criteria and sub-criteria can be considered in the selection process. Among a number of MCDM approaches, the fuzzy set theory and best-worst method (BWM) are integrated as the fuzzy BWM in this study to structure the new product idea selection process under a group decision-making process. The hierarchy structure for the new product idea selection is also established to consider the perspectives of finance, marketing, engineering, manufacturing, and sustainability. Overall speaking, this study contributes to the field of NPD through overcoming the new product idea selection problem, while the group decision-making process is incorporated into the fuzzy BWM.

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“…The assumption is proposed here that the positive and negative ideal solutions equal the optimal and worst values correspondingly, as described in Equations (17) and (18).…”

Section: Comprehensive Evaluation Based On Interval Type-ii Fuzzy Ahpmentioning

confidence: 99%

“…Modern intelligent techniques principally consist of an artificial neural network (ANN), a support vector machine (SVM), the least-squares support vector machine (LSSVM), and so on [16]. Due to the mature theory and accurate calculation of traditional evaluation methods and the quick processing capability of intelligent algorithms [17][18][19], this study has established a combined assessment approach where interval type-II fuzzy integrated with the analytic hierarchy process (AHP) is employed for index weight determination, and technique for order preference by similarity to an ideal solution (TOPSIS) is applied for comprehensive estimation and ranking. With regard to intelligent evaluation techniques, an ANN is confronted with slow convergence speed and easily falls into a local optimum [20].…”

Section: Introductionmentioning

confidence: 99%

Sustainability Evaluation of Renewable Energy Incubators Using Interval Type-II Fuzzy AHP-TOPSIS with MEA-MLSSVM

2021

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With the development of renewable energy, renewable energy incubators have emerged continuously. However, these incubators present a crude development model of low-level replication and large-scale expansion, which has triggered a series of urgent problems including unbalanced regional development, low incubation efficiency, low resource utilization, and vicious competition for resources. There are huge challenges for the sustainable development of incubators in the future. A scientific and accurate evaluation approach is of great significance for improving the sustainability of renewable energy incubators. Therefore, this paper proposes a novel method combining an interval type-II fuzzy analytic hierarchy process (AHP) with mind evolutionary algorithm-modified least-squares support vector machine (MEA-MLSSVM). The indicator system is established from two aspects: service capability and operational efficiency. TOPSIS integrated with an interval type-II fuzzy AHP is employed for index weighting and assessment. In the least-squares support vector machine (LSSVM), the traditional radial basis function is replaced with the wavelet transform function (WT), and the parameters are fine-tuned by the mind evolutionary algorithm (MEA). Accordingly, the establishment of a comprehensive sustainability evaluation model for renewable energy incubators is accomplished in this paper. The experimental study reveals that this novel technique has the advantages of scientificity and precision and provides a decision-making basis for renewable energy incubators to realize sustainable operation.

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A New Coefficient of Rankings Similarity in Decision-Making Problems

Cited by 170 publications

References 36 publications

Bonferroni Prioritized Aggregation Operators Applied to Government Transparency

Bonferroni Prioritized Aggregation Operators Applied to Government Transparency

New Product Idea Selection in the Fuzzy Front End of Innovation: A Fuzzy Best-Worst Method and Group Decision-Making Process

Sustainability Evaluation of Renewable Energy Incubators Using Interval Type-II Fuzzy AHP-TOPSIS with MEA-MLSSVM

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