本文選題：綜合評價 + 動態(tài)評價��； 參考：《系統(tǒng)工程學報》2017年02期

【摘要】：針對動態(tài)激勵評價問題,提出了一種誘導(dǎo)被評價對象個體行為向評價者全局期望動態(tài)趨同的評價方法.首先,通過對全局被評價對象的觀測值與變化量進行"激勵型分層"得到具有獎優(yōu)懲拙思想的"全局激勵系數(shù)",據(jù)此在動態(tài)環(huán)境中集結(jié)出帶有激勵作用的被評價對象綜合評價值與排序.然后,運用一個算例對該方法的可行性與有效性進行了說明.此外,通過對激勵策略進行仿真,分析不同策略下相對初始排序的變化程度及不同策略間的變動對排序結(jié)果的影響,從而為評價者制定激勵型分層策略提供理論依據(jù).
[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.
【作者單位】： 東北大學工商管理學院;
【基金】：國家自然科學基金資助項目(71071030;71071031);國家自然科學基金面上資助項目(71671031)
【分類號】：C934
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本文編號：2072533