摘要
Consistency and the weights estimation model of the interval number comparison matrix (INCM) in the analytical hierarchy process is studied under uncertainty decision-making case. Based on the weights feasible region, the local consistency definition and the local satisfactory consistency definition are given. Then, a computational model set up to test whether the INCM has the local satisfactory consistency or not. Moreover, the consistency degree based on the random crisp comparison matrix is defined as an effective index to test the consistency. Next, the upper range model, the lower range model, and the possible value model are put forward which can solve the problem that some existing approaches do not consider the consistency and its effect on the weights. According to the property of these models, a genetic algorithm is developed.
Consistency and the weights estimation model of the interval number comparison matrix (INCM) in the analytical hierarchy process is studied under uncertainty decision-making case. Based on the weights feasible region, the local consistency definition and the local satisfactory consistency definition are given. Then, a computational model set up to test whether the INCM has the local satisfactory consistency or not. Moreover, the consistency degree based on the random crisp comparison matrix is defined as an effective index to test the consistency. Next, the upper range model, the lower range model, and the possible value model are put forward which can solve the problem that some existing approaches do not consider the consistency and its effect on the weights. According to the property of these models, a genetic algorithm is developed.
出处
《自动化学报》
EI
CSCD
北大核心
2005年第3期434-439,共6页
Acta Automatica Sinica
基金
国家高技术研究发展计划(863计划)，Doctor Startup Fund of Liaoning Province，国家自然科学基金
关键词
集成模型
区间数
求解
权重
矩阵
Genetic algorithms
Mathematical models
Matrix algebra
Parameter estimation
Random processes
Theorem proving
