软集群矩形方法用于在多标准决策中获得标准权重
Shervin Zakeri1, Dimitri Konstantas2, Prasenjit Chatterjee3,4
1Geneva School of Economics and Management, University of Geneva, 1211, Geneva, Switzerland. Shervin.Zakeri@unige.ch.
本研究介绍了软集群-矩形 (SCR) 方法用于多标准决策 (MCDM),解决不确定性并避免对对比. 这种新的方法产生了可靠的标准权重,与混合方法相美.
科学领域:
- 决策科学 决策科学
- 运营研究 运营研究
- 人工智能的人工智能
背景情况:
- 多标准决策 (MCDM) 中的主观权重方法依赖于决策者的投入.
- 这些方法因输入不确定性和对对比而面临挑战,影响了权重可靠性.
研究的目的:
- 引入一种新的MCDM方法,软集群-矩形 (SCR),以克服现有的主观权重技术的局限性.
- 解决不确定性,避免在标准权重确定中对对进行比较.
主要方法:
- 该SCR方法使用模糊逻辑和分析几何学,避免对对比.
- 权重是根据三个集群 (非物质,平,重要) 的标准会员价值计算的.
- 涉及矩形面积的几何计算确定了最终的重量.
主要成果:
- 在没有对对比的情况下,SCR方法成功地确定了标准权重.
- 结果显示,与传统的主观方法相比,不确定性降低了.
- 结果显示与客观权重技术的相似之处,与混合方法的可比结果.
结论:
- SCR方法为MCDM中标准权重提供了一个可靠的替代方案.
- 它有效地处理不确定性,并避免双对比的陷.
- 该方法在诸如自动驾驶汽车路线选择等应用中显示出前景.
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