江西理工大学学报
江西理工大學學報
강서리공대학학보
Journal of Jiangxi University of Science and Technology
2015年
5期
74-79
,共6页
优化算法%演化算法%混沌搜索%花粉授粉算法
優化算法%縯化算法%混沌搜索%花粉授粉算法
우화산법%연화산법%혼돈수색%화분수분산법
optimization algorithm%evolutionary algorithm%chaotic search%flower pollination algorithm
针对基本FPA算法在求解复杂工程优化问题时存在收敛速度慢的缺点,提出应用精英混沌搜索的花粉授粉算法(CSFPA). CSFPA算法在搜索过程中从当前种群中随机选择出一个个体,对其执行精英混沌搜索操作,从而加快算法的收敛速度. 将提出的CSFPA算法与基本FPA 算法在几个国际上常用的基准测试问题上进行了比较实验,实验结果表明CSFPA算法能够在大多数测试问题上比基本FPA算法获得更优的结果.
針對基本FPA算法在求解複雜工程優化問題時存在收斂速度慢的缺點,提齣應用精英混沌搜索的花粉授粉算法(CSFPA). CSFPA算法在搜索過程中從噹前種群中隨機選擇齣一箇箇體,對其執行精英混沌搜索操作,從而加快算法的收斂速度. 將提齣的CSFPA算法與基本FPA 算法在幾箇國際上常用的基準測試問題上進行瞭比較實驗,實驗結果錶明CSFPA算法能夠在大多數測試問題上比基本FPA算法穫得更優的結果.
침대기본FPA산법재구해복잡공정우화문제시존재수렴속도만적결점,제출응용정영혼돈수색적화분수분산법(CSFPA). CSFPA산법재수색과정중종당전충군중수궤선택출일개개체,대기집행정영혼돈수색조작,종이가쾌산법적수렴속도. 장제출적CSFPA산법여기본FPA 산법재궤개국제상상용적기준측시문제상진행료비교실험,실험결과표명CSFPA산법능구재대다수측시문제상비기본FPA산법획득경우적결과.
Flower pollination algorithm (FPA) is an emerging function optimization algorithm. However, the traditional FPA tends to suffer from slow convergence when solving complex engineering optimization problems. Aiming at this weakness of the basic FPA, an enhanced flower pollination algorithm based on elite chaotic search (CSFPA) is proposed in this paper. In the evolution process, CSFPA randomly selects an individual to execute the elite chaotic search strategy, which can accelerate the convergence speed. In the experiments, the proposed CSFPA is compared with the basic FPA on several benchmark test problems. The experimental results validate the effectiveness of the proposed CSFPA.
