發(fā)布時間：2018-09-07 22:01

【摘要】：提出一種協(xié)調(diào)探索和開發(fā)能力的灰狼優(yōu)化算法.利用佳點集方法初始化灰狼個體的位置,為全局搜索多樣性奠定基礎(chǔ);為協(xié)調(diào)算法的全局探索和局部開發(fā)能力,給出一種基于正切三角函數(shù)描述的非線性動態(tài)變化控制參數(shù);為加快算法的收斂速度,受粒子群優(yōu)化算法個體記憶功能的啟發(fā),設(shè)計一種新的個體位置更新公式.10個標準函數(shù)的測試結(jié)果表明,改進灰狼優(yōu)化(IGWO)算法能夠有效地協(xié)調(diào)其對問題搜索空間的探索和開發(fā)能力.
[Abstract]:A grey wolf optimization algorithm is proposed to coordinate exploration and development. The optimal point set method is used to initialize the individual position of the gray wolf, which lays the foundation for global search for diversity, and provides a nonlinear dynamic change control parameter based on tangent trigonometric function for coordinating the global exploration and local development of the algorithm. In order to speed up the convergence of the algorithm and inspired by the individual memory function of the particle swarm optimization algorithm, a new updating formula of individual position is designed. The test results of 10 standard functions show that, The improved gray wolf optimization (IGWO) algorithm can effectively coordinate its ability to explore and develop the search space of the problem.
【作者單位】： 貴州財經(jīng)大學(xué)貴州省經(jīng)濟系統(tǒng)仿真重點實驗室;貴州財經(jīng)大學(xué)數(shù)學(xué)與統(tǒng)計學(xué)院;湖南人文科技學(xué)院能源與機電工程學(xué)院;
【基金】：國家自然科學(xué)基金項目(61463009) 商務(wù)部與貴州財經(jīng)大學(xué)聯(lián)合基金項目(2016SWBZD13) 貴州省科學(xué)技術(shù)基金項目(黔科合基礎(chǔ)[2016]1022) 湖南省自然科學(xué)基金項目(2016JJ3079) 湖南省教育廳青年基金項目(14B097)
【分類號】：TP18
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本文編號：2229535