OTHER
Practical common weights goal programming approach for technology selection
Alireza Alinezhad, R Kiani Mavib
- 发表年份
- 2009
- 引用次数
- 5
摘要
A practical common weight goal programming methodology with an improved discriminating power for technology selection is introduced. The proposed goal programming methodology enables the evaluation of the relative eciency of decisionmaking units (DMUs) with respect to multiple outputs and a single exact input with common weights. Its robustness and discriminating power are illustrated via a previously reported robot evaluation problem by comparing the ranking obtained by the proposed goal programming framework with that obtained by the DEA classic model (CCR model) and Minimax method (Karsak and Ahiska (2005)).
关键词
Goal programmingMinimaxRobustness (evolution)Mathematical optimizationRanking (information retrieval)Selection (genetic algorithm)Computer scienceLinear programmingArtificial intelligenceMachine learning
相关论文
OTHER
📊 26,957 引用
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
PERCEPTION
📊 22,245 引用
Artificial intelligence: a modern approach
1995
OTHER
开放获取📊 20,501 引用
Fractional Differential Equations
Igor Podlubný
2025
OTHER
📊 18,993 引用
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991