Performance evaluation models for parallel computing with dual hesitant fuzzy information

Article type: Research Article

Authors: Zhang, Ye^{a; b; *}

Affiliations: [a] College of Computer and Information, Hohai University, Nanjing, P.R. China | [b] Agricultural and Animal Husbandry College of Tibet University, Tibet, P.R. China

Correspondence: [*] Corresponding author. Ye Zhang, No.8, Fo-Cheng-Xi Road, Nanjing 211100, P.R. China. Tel.: +86 25 58099106; Fax: +86 25 58099124; E-mail: [email protected].

Abstract: The problem of evaluating the performance of parallel computing with dual hesitant fuzzy information denotes the multiple attribute decision making issues. Afterwards, inspired by the method of Hamacher aggregation operators and the Choquet integral, in this work, we design a dual hesitant fuzzy Hamacher correlated average (DHFHCA) operator. Next, we exploit the proposed operator to implement the model to tackle the dual hesitant fuzzy multiple attribute decision making problem. In the end, an example is presented to evaluate performance of the proposed method.

Keywords: Multiple attribute decision making, dual hesitant fuzzy values, dual hesitant fuzzy Hamacher correlated average (DHFHCA) operator, performance of parallel computing

DOI: 10.3233/IFS-151919

Journal: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 4, pp. 2067-2071, 2016