基于全局信息的动态激励评价方法及激励策略

发布时间：2018-06-27 03:43

  本文选题：综合评价 + 动态评价　； 参考：《系统工程学报》2017年02期

【摘要】：针对动态激励评价问题,提出了一种诱导被评价对象个体行为向评价者全局期望动态趋同的评价方法.首先,通过对全局被评价对象的观测值与变化量进行"激励型分层"得到具有奖优惩拙思想的"全局激励系数",据此在动态环境中集结出带有激励作用的被评价对象综合评价值与排序.然后,运用一个算例对该方法的可行性与有效性进行了说明.此外,通过对激励策略进行仿真,分析不同策略下相对初始排序的变化程度及不同策略间的变动对排序结果的影响,从而为评价者制定激励型分层策略提供理论依据.
[Abstract]:In order to solve the problem of dynamic incentive evaluation, an evaluation method is proposed to induce the individual behavior of the evaluated object to converge to the overall expectation of the evaluator. First Through the "incentive stratification" of the observed value and variation of the global evaluated object, the "global incentive coefficient" with the idea of reward, merit and punishment is obtained, according to which the evaluated object with incentive function is assembled in the dynamic environment. Value and ranking. Then, an example is used to illustrate the feasibility and effectiveness of the method. In addition, through the simulation of incentive strategies, this paper analyzes the degree of relative initial ranking under different strategies and the influence of the changes between different strategies on the ranking results, thus providing a theoretical basis for the evaluators to formulate incentive stratification strategies.
【作者单位】： 东北大学工商管理学院;
【基金】：国家自然科学基金资助项目(71071030;71071031);国家自然科学基金面上资助项目(71671031)
【分类号】：C934
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本文编号：2072533