精确排序技术(TARO):一种新的多准则分析方法,用于工业搬运机器人的性能评价

IF 1.4 Q3 OPERATIONS RESEARCH & MANAGEMENT SCIENCE
Bipradas Bairagi
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引用次数: 2

摘要

排序反转是决策过程中常见的一种现象,尤其在多个多准则决策(MCDM)技术独立应用的情况下,会导致选择过程中的混乱和歧义。为了消除这种混乱,本文提出了一种新的MCDM方法,即精确排序技术(TARO)。TARO方法是传统MCDM方法的扩展。提出的方法从传统方法的最后开始,最终选择值。所提出的技术,使用一种先进的熵权法,首先测量最终选择值的权重。然后,根据最终的截面值及其计算的权重,TARO测量准确的选择指标,确定备选方案的准确排名顺序。通过三个机器人选择问题的实例说明了该方法的有效性。TARO的结果证明了所提出的技术在MCDM环境下正确决策的有效性、适用性和要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Technique of Accurate Ranking Order (TARO): A novel multi criteria analysis approach in performance evaluation of industrial robots for material handling
Rank reversal in decision making is a common phenomenon resulting in confusion and ambiguity in selection procedure especially while multiple multi-criteria decision making (MCDM) techniques are independently applied. To eradicate this confusion, this paper proposes a novel MCDM methodology namely Technique of Accurate Ranking Order (TARO). The TARO method is an extension of conventional MCDM approaches. The proposed method commences at the end of conventional methodologies with the final selection values. The proposed technique, using an advanced version of entropy weighting method, initially measures weights of the final selection values. Subsequently, based on the final section values and their computed weights, TARO measures accurate selection indices that determine the accurate ranking order of the alternatives. The proposed technique is illustrated by three real life examples on robot selection problems. The results obtained by TARO justify the validity, applicability and requirements of the proposed techniques for proper decision making under the MCDM environment.
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来源期刊
Decision Science Letters
Decision Science Letters Decision Sciences-Decision Sciences (all)
CiteScore
3.40
自引率
5.30%
发文量
49
审稿时长
20 weeks
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