一种基于左和右分数的新ELECTRE方法,用于多标准决策
Faeze Jokar1, M Jalali Varnamkhasti1, A Hadi-Vencheh1
1Department of Mathematics, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran.
Computational intelligence and neuroscience
|November 29, 2023
概括
这项研究通过结合间隔模糊数来增强ELECTRE (消除和选择翻译现实) 多标准决策方法. 改进的方法解决了传统ELECTRE的弱点,提供了更完整的系统性能排名.
科学领域:
- 运营研究 运营研究
- 决策科学 决策科学 决策科学
背景情况:
- 多标准决策 (MCDM) 对于系统性能评估至关重要.
- ELECTRE (消除和选择翻译现实) 方法是广泛使用的MCDM技术.
- 经典的ELECTRE有其局限性,包括值依赖和不完整的排名结果.
研究的目的:
- 解决传统的ELECTRE方法的弱点.
- 通过使用间隔模糊数来引入一种增强的ELECTRE方法.
- 提高系统性能排名的完整性和准确性.
主要方法:
- 通过整合间隔模糊数来修改ELECTRE方法.
- 开发一种基于模糊的方法来处理决策中的不确定性.
- 使用左和右间隔数来改进协调分析.
主要成果:
- 拟议的间隔模糊ELECTRE方法克服了经典方法的局限性.
- 证明能够提供更完整和最终的排名的能力.
- 通过先前研究的例子验证了有效性.
结论:
- 间隔模糊数方法显著增强了ELECTRE方法.
- 这种基于模糊的ELECTRE技术为MCDM问题提供了更强大的解决方案.
- 改进的方法提供了卓越的系统性能排名能力.
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