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author:

Pan, Xiao-Hong (Pan, Xiao-Hong.) [1] | He, Shi-Fan (He, Shi-Fan.) [2] | Wang, Ying-Ming (Wang, Ying-Ming.) [3] (Scholars:王应明) | Chin, Kwai-Sang (Chin, Kwai-Sang.) [4]

Indexed by:

EI SCIE

Abstract:

To achieve sustainable management of municipal solid waste, selecting an appropriate waste to energy (WTE) technology is pivotal. The WTE technology selection is a complicated issue because it involves a range of conflicting criteria and a rich diversity of stakeholders. Moreover, the complexity will be multiplied when considering that the preference information provided by different people with respect to different criteria takes different forms and granularities. To tackle the WTE technology selection problems with multi granular hybrid information, this paper proposes a new group decision-making framework. The proposed framework provides a reasonable solution to the WTE technology selection problems through four stages. In the first stage, three information transformation mechanisms are established to transform information in different forms and granularities into unified belief structures. In the second stage, a symmetrical cross-entropy measure based weight determination model is developed to calculate the criteria weights. In the third stage, by combining information transformation mechanisms and criteria weights, the analytical evidential reasoning algorithm is extended to generate group opinions. Finally, according to the generated group opinions, the expected utilities of alternatives are calculated to compare and rank the alternatives. To illustrate the implementation process of the proposed decision-making framework, an application about the WTE technology selection in China is performed. Besides, a comparative experiment is conducted to show the flexibility and reliability of our proposal. (C) 2021 Elsevier Inc. All rights reserved.

Keyword:

Evidential reasoning algorithm Multi-granular hybrid information Symmetrical cross-entropy measure Waste to energy

Community:

  • [ 1 ] [Pan, Xiao-Hong]Fuzhou Univ, Decis Sci Inst, Fujian 350116, Peoples R China
  • [ 2 ] [He, Shi-Fan]Fuzhou Univ, Decis Sci Inst, Fujian 350116, Peoples R China
  • [ 3 ] [Wang, Ying-Ming]Fuzhou Univ, Decis Sci Inst, Fujian 350116, Peoples R China
  • [ 4 ] [Wang, Ying-Ming]Fuzhou Univ, Key Lab Spatial Data Min & Informat Sharing, Minist Educ, Fuzhou, Peoples R China
  • [ 5 ] [Pan, Xiao-Hong]City Univ Hong Kong, Dept Syst Engn & Engn Management, Hong Kong, Peoples R China
  • [ 6 ] [Chin, Kwai-Sang]City Univ Hong Kong, Dept Syst Engn & Engn Management, Hong Kong, Peoples R China

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Source :

INFORMATION SCIENCES

ISSN: 0020-0255

Year: 2022

Volume: 587

Page: 450-472

8 . 1

JCR@2022

0 . 0 0 0

JCR@2023

ESI Discipline: COMPUTER SCIENCE;

ESI HC Threshold:61

JCR Journal Grade:1

CAS Journal Grade:1

Cited Count:

WoS CC Cited Count: 10

SCOPUS Cited Count: 11

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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