發(fā)布時(shí)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(diǎn)集方法初始化灰狼個(gè)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(dòng)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(gè)體記憶功能的啟發(fā),設(shè)計(jì)一種新的個(gè)體位置更新公式.10個(gè)標(biāo)準(zhǔn)函數(shù)的測(cè)試結(jié)果表明,改進(jìn)灰狼優(yōu)化(IGWO)算法能夠有效地協(xié)調(diào)其對(duì)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(cái)經(jīng)大學(xué)貴州省經(jīng)濟(jì)系統(tǒng)仿真重點(diǎn)實(shí)驗(yàn)室;貴州財(cái)經(jīng)大學(xué)數(shù)學(xué)與統(tǒng)計(jì)學(xué)院;湖南人文科技學(xué)院能源與機(jī)電工程學(xué)院;
【基金】：國(guó)家自然科學(xué)基金項(xiàng)目(61463009) 商務(wù)部與貴州財(cái)經(jīng)大學(xué)聯(lián)合基金項(xiàng)目(2016SWBZD13) 貴州省科學(xué)技術(shù)基金項(xiàng)目(黔科合基礎(chǔ)[2016]1022) 湖南省自然科學(xué)基金項(xiàng)目(2016JJ3079) 湖南省教育廳青年基金項(xiàng)目(14B097)
【分類號(hào)】：TP18
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本文編號(hào)：2229535