Semantic Scholar Open Access 2016 7 sitasi

Majority Clusters‐Density Ordered Weighting Averaging: A Family of New Aggregation Operators in Group Decision Making

Wei-Wei Li Pingtao Yi Yajun Guo

Lihat Sumber DOI

Abstrak

In the process of aggregation, it is necessary, especially for group decision‐making (GDM) problems, to consider distributed characteristic hidden in aggregates. In this case, clustering has been a common way for discovering the implicit distributed structures. This paper mainly investigates the characteristic of majority clusters, rather than majority elements and develops a new class of aggregation operators denominated majority clusters density‐ordered weighting averaging (MC‐DOWA) operators. Furthermore, we discuss properties of these operators and calculate the associated weights. Finally, a numerical example is provided to illustrate the application of the MC‐DOWA operators, and the aggregations are compared with those of the other three aggregation operators: majority additive‐OWA (MA‐OWA), dependent OWA (DOWA) and cluster‐based DOWA (Clus‐DOWA) operators.

Topik & Kata Kunci

Computer Science Mathematics

Penulis (3)

Wei-Wei Li

Pingtao Yi

Yajun Guo

Format Sitasi

APA MLA BibTeX

Li, W., Yi, P., Guo, Y. (2016). Majority Clusters‐Density Ordered Weighting Averaging: A Family of New Aggregation Operators in Group Decision Making. https://doi.org/10.1002/int.21821

Akses Cepat

Lihat di Sumber doi.org/10.1002/int.21821

Informasi Jurnal

Tahun Terbit: 2016
Bahasa: en
Total Sitasi: 7×
Sumber Database: Semantic Scholar
DOI: 10.1002/int.21821
Akses: Open Access ✓