A combination weighting model based on iMOEA/D-DE

作     者：Mingtao DONG Jianhua CHENG Lin ZHAO Mingtao DONG;Jianhua CHENG;Lin ZHAO

作者机构：College of Intelligent Systems Science and EngineeringHarbin Engineering UniversityHarbin150001China 

出 版 物：《Frontiers of Information Technology & Electronic Engineering》 (信息与电子工程前沿（英文版）)

年 卷 期：2022年第23卷第4期

页      面：604-616页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 0808[工学-电气工程] 081104[工学-模式识别与智能系统] 08[工学] 080401[工学-精密仪器及机械] 081105[工学-导航、制导与控制] 0804[工学-仪器科学与技术] 0835[工学-软件工程] 0825[工学-航空宇航科学与技术] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the National Natural Science Foundation of China(Nos.61633008,61773132,and 61803115) the 7th Generation Ultra Deep Water Drilling Unit Innovation Project Sponsored by Chinese Ministry of Industry and Information Technology,the Heilongjiang Provincial Science Fund for Distinguished Young Scholars,China(No.JC2018019) the Fundamental Research Funds for the Central Universities,China(No.HEUCFP201768) 

主　　题：Combination weighting MOEA/D-DE Game theory Self-learning ability Relative entropy 

摘      要：This paper proposes a combination weighting(CW)model based on iMOEA/D-DE(i.e.,improved multiobjective evolutionary algorithm based on decomposition with differential evolution)with the aim to accurately compute the weight of evaluation ***-expert weight considers only subjective weights,leading to poor *** overcome this shortcoming,a multiobjective optimization model of CW based on improved game theory is proposed while considering the uncertainty of combination *** improved mutation operator is introduced to improve the convergence speed,and thus better optimization results are ***,an adaptive mutation constant and crossover probability constant with self-learning ability are proposed to improve the robustness of MOEA/*** the existing weight evaluation approaches cannot evaluate weights separately,a new weight evaluation approach based on relative entropy is *** the evaluation method of integrated navigation systems as an example,certain experiments are carried *** is proved that the proposed algorithm is effective and has excellent performance.