Evidence map›Paper›PMID 34567279›Full record

ArticleInternational journal of machine learning and cybernetics2022

A collaborative emergency decision making approach based on BWM and TODIM under interval 2-tuple linguistic environment.

Kaixuan Qi, Hua Chai, Qiangling Duan, Yongjian Du, Qingsong Wang, Jinhua Sun, K M Liew

Abstract read
In one paragraph

Article in International journal of machine learning and cybernetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Kaixuan QiState Key Laboratory of Fire Science, University of Science and Technology of China, Hefei, 230026 China.ORCID 0000-0001-9223-977X
Hua ChaiEmergency Management Training Center, Party School of the Central Committee of C.P.C (National Academy of Governance), Beijing, 100091 China.
Qiangling DuanState Key Laboratory of Fire Science, University of Science and Technology of China, Hefei, 230026 China.
Yongjian DuState Key Laboratory of Fire Science, University of Science and Technology of China, Hefei, 230026 China.
Qingsong WangState Key Laboratory of Fire Science, University of Science and Technology of China, Hefei, 230026 China.
Jinhua SunState Key Laboratory of Fire Science, University of Science and Technology of China, Hefei, 230026 China.
K M LiewDepartment of Architecture and Civil Engineering, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Emergencies require various emergency departments to collaborate to achieve timely and effective emergency responses. Thus, the overall performance of emergency response is influenced not only by the efficiency of each department alternative but also by the coordination effect among different department alternatives. This paper proposes a collaborative emergency decision making (CEDM) approach considering the synergy among different department alternatives based on the best-worst method (BWM) and TODIM (an acronym in Portuguese of interactive and multiple attribute decision making) method within an interval 2-tuple linguistic environment. First, the evaluation information provided by decision makers (DMs) is represented by interval 2-tuple linguistic variables to reflect and model the underlying diversity and uncertainty. On the basis of the DMs' evaluations, the individual and collaborative performance evaluations of multi-alternative combinations composed of different department alternatives are constructed. Then, the BWM is extended into interval 2-tuple linguistic environment to obtain the weights of evaluation criteria, where the group decision making is taken into account in an interval fuzzy mathematical programming model. Furthermore, to derive more practical and accurate decision results, an interval 2-tuple linguistic TODIM (ITL-TODIM) method is proposed by considering the DMs' psychological behaviours. In the developed ITL-TODIM method, both the gain and loss degrees of one alternative relative to another are simultaneously computed. Finally, a numerical example is presented to illustrate the applicability of the proposed method. Sensitivity and comparative analyses are also provided to demonstrate the effectiveness and advantages of the proposed approach.

Indexed as

Best–worst method (BWM)Emergency decision makingInterval 2-tuple linguisticMultiple criteria decision makingTODIM

Identifiers

PMID34567279
PMCPMC8449834

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.