摘要
当多目标系统中的决策目标和备选方案都较多时,决策分析就相当耗时费力。本文以决策论中的理想目标作为监督信息,利用模糊聚类分析中的部分监督模糊C-均值聚类算法,提出一种新的多目标决策方法,该方法不仅能识别最佳方案,而且能确定各备选方案的排序,以及属于理想目标的程度。
Based on being decision making multi - objective and spare multi - project in multi - objective system, decision making analysis is considerably time - consuming and laborious. Ideal objective in decision making theory is regarded as supervised information, a new multi - objective decision making method utilizing partial supervised and weighted fuzzy C- means algorithm of fuzzy clustering analysis has been proposed in this paper, the method is not only able to identify optimal project, but also to ascertain order and degree of attributing to ideal objective about spare projects, The rationality of decision making analysis in multi - objective system with the method has been testified by simulation example.
出处
《西安财经学院学报》
2005年第4期31-34,共4页
Journal of Xi’an University of Finance & Economics
基金
四川省教育厅高教委员会课题项目(200136)。
关键词
决策分析
多目标决策
模糊聚类分析
部分监督模糊C-均值聚类算法
decision making analysis, multi -objective decision making, fuzzy clustering analysis, partial supervised and weighted fuzzy C - means algorithm
