New intelligent optimization framework

作     者：Xie, As 

作者机构：Zhejiang Univ Technol China Inst SMEs Hangzhou Zhejiang Peoples R China 

出 版 物：《AUTOMATIKA》 (Autom.)

年 卷 期：2018年第59卷第2期

页      面：231-253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] 08[工学] 0811[工学-控制科学与工程] 

基　　金：research fund from "Collaborative innovation centre for Transformation and Upgrading of Micro, Small and Medium Enterprises, Zhejiang University of Technology" [16JDGH048] Zhejiang Provincial Key Research Base of Philosophy and Social Sciences-Research Centre for Technology Innovation and Enterprise Internationalization 

主　　题：Intelligent optimization optimization algorithm meta-heuristic method encoding scheme benchmarking philosophy 

摘      要：Generally, the intelligence of the intelligent optimization algorithms is mainly dependent on the probability and operational rules. Thus there are always some probability equations or mathematical formulations that need to be updated. This paper proposes an algorithm model that needs no probability tuning. The algorithm designed according to the guiding principles and specific methods of benchmarking proposed in this paper is able to achieve the synergistic coexistence and automatic balance of exploration and exploitation, thus the population diversity will be kept during the running. The algorithm model proposed here is between engineering technology and cognitive philosophy, it is not just a specific algorithm, but a kind of general methodology and/or a mode of thinking. The successful application of some realistic issues, like distributed power generation optimization configuration, verified its applicability.