Standard deviation and rank sum-based MARCOS model under intuitionistic fuzzy information for hospital site selection

排名(信息检索) 加权 秩(图论) 阿卡克信息准则 运筹学 计算机科学 集合(抽象数据类型) 选择(遗传算法) 多准则决策分析 标准差 数据挖掘 统计 数学 人工智能 医学 组合数学 放射科 程序设计语言
作者
Ibrahim M. Hezam,Anand Kumar Mishra,Dragan Pamučar,Pratibha Rani,Arunodaya Raj Mishra
出处
期刊:Kybernetes [Emerald Publishing Limited]
卷期号:53 (10): 3727-3753 被引量:7
标识
DOI:10.1108/k-01-2023-0136
摘要

Purpose This paper develops a decision-analysis model to prioritize and select the site to establish a new hospital over different indicators such as cost, market conditions, environmental factors, government factors, locations and demographics. In this way, an integrated model is proposed under the intuitionistic fuzzy information (IFI), the standard deviation (SD), the rank-sum (RS) and the measurement of alternatives and ranking using the compromise solution (MARCOS) approach for ranking hospital sites (HSs). Design/methodology/approach The IF-SD-RS model is presented to obtain the combined weight with the objective and subjective weights of diverse sub-criteria and indicators for ranking sites to establish the hospital. The IF-MARCOS model is discussed to prioritize the various sites to establish the hospital over several crucial indicators and sub-criteria. Findings The authors implement the developed model on a case study of HSs assessment for the construction of new hospital. In this regard, inclusive set of 6 key indicators and 18 sub-criteria are considered for the evaluation of HSs. This study distinguished that HS ( h 2 ) with combined utility function 0.737 achieves highest rank compared to the other three sites for the given information. Sensitivity analysis is discussed with different parameter values of sub-criteria to examine how changes in weight parameter ratings of the sub-criteria affect the prioritization of the options. Finally, comparative discussion is made with the diverse extant models to show the reasonability of the developed method. Originality/value This study aims to develop an original hybrid weighting tool called the IF-SD-RS model with the integration of IF-SD and IF-RS approaches to find the indicators' weights for prioritizing HSs. The developed integrated weighting model provides objective weight by IF-SD and subjective weight with the IF-RS model. The model presented in the paper deals with a consistent multi-attribute decision analysis (MADA) concerning the relations between indicators and sub-criteria for choosing the appropriate options using the developed IF-SD-RS-MARCOS model.
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