改进的离差最大化决策模型及其在临近空间多任务规划中的应用

一些常用的多属性决策方法在处理多属性评价问题时，易出现评价结果相近，评价值差异较小、区分度不高等问题. 运用离差最大化思想构建的多属性决策模型，能有效拉大评价值间的差异，便于决策方案的优选和排序. 但该模型在实践中，只考虑了因属性值差异性引起的可变权重，忽略了评价指标本身的属性权重，易造成评价结果偏离真实结果. 鉴于此，对已有的基于离差最大化的多属性决策模型进行改进，综合考虑评价属性的可变权重和属性权重，设计了改进的离差最大化决策模型，并将该模型应用于临近空间多任务系统综合效能评估中，为临近空间多任务规划方案的排序及优选提供决策支持. 最后，通过算例，对比验证了该模型具有一定的适用性.

Improved maximizing deviation decision-making model and its application in multi-mission planning of near space system

In the process of multiple attribute evaluation using traditional multi-attribute decision method, some problems such as that the evaluation results are close to each other, the evaluation values differ to each other scarcely, the difference between these evaluations is not obvious and so on can easily occur in practice. Although the multiple attribute decision model based on maximizing deviation can enlarge the evaluation values discrepancy for the optimizing and ranking of the decision making schemes, it only considers the variable weight caused by the discrepancy of the attribute values and neglects the weight of the evaluation indicator itself in practice, causing that the evaluation results easily deviate the actual results. In view of this, the paper makes further amendments to the multi-attribute decision making model based on maximizing deviation. After considering the weighted weight and the weight of the evaluation attribute completely, the author designs an improved maximizing deviation decision making model and applies the model to the comprehensive effectiveness evaluation of the multi-mission planning of near space system, which can provide decision support for the selection and optimization of the multi-mission planning schemes of near space system. Finally, the model is proved to have certain applicability by the case analysis.