计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2015年
2期
57-59,75
,共4页
免疫优化%多峰函数%种群分布%局部搜索%均匀设计
免疫優化%多峰函數%種群分佈%跼部搜索%均勻設計
면역우화%다봉함수%충군분포%국부수색%균균설계
immune optimization%multi-model function%population distribution%local search%uniform design
为了尽可能多地求得多峰函数的全部最优解，提出了基于均匀设计的免疫克隆多峰函数优化。算法采用均匀设计初始化种群，保证初始抗体群体分布的均匀性和多样性。采用Larmark学习策略对群体进行局部搜索，以增强算法的收敛速度和搜索精度。在免疫克隆参数设置上，将参数设定问题描述成多因素多水平的均匀设计问题，减少设置参数所需的实验次数。实验结果表明，该算法寻优能力较强。
為瞭儘可能多地求得多峰函數的全部最優解，提齣瞭基于均勻設計的免疫剋隆多峰函數優化。算法採用均勻設計初始化種群，保證初始抗體群體分佈的均勻性和多樣性。採用Larmark學習策略對群體進行跼部搜索，以增彊算法的收斂速度和搜索精度。在免疫剋隆參數設置上，將參數設定問題描述成多因素多水平的均勻設計問題，減少設置參數所需的實驗次數。實驗結果錶明，該算法尋優能力較彊。
위료진가능다지구득다봉함수적전부최우해，제출료기우균균설계적면역극륭다봉함수우화。산법채용균균설계초시화충군，보증초시항체군체분포적균균성화다양성。채용Larmark학습책략대군체진행국부수색，이증강산법적수렴속도화수색정도。재면역극륭삼수설치상，장삼수설정문제묘술성다인소다수평적균균설계문제，감소설치삼수소수적실험차수。실험결과표명，해산법심우능력교강。
In order to get all the best solutions of multi-model function, an immune clonal algorithm with uniform design for multi-modal function optimization problem is proposed. Uniform design is used to initialize the population so that the initialization population is uniform and with diversity. In addition, Lamarck learning is used as a local search strategy to enhance the search ability for the optimal solution. Uniform design is used to convert parameter establishment problem into the experimental design of multi-factor and multi-level, it can reduce the test times of simulation experiments. The experi-mental results show that the algorithm has better optimization ability.
