跳跃海豚群算法
Jumping dolphin swarm algorithm
摘要点击 104  全文点击 121  投稿时间:2018-06-27  修订日期:2019-01-19
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DOI编号  10.7641/CTA.2019.80474
  2019,36(10):1755-1767
中文关键词  海豚群算法  函数优化  长度自适应策略  跳跃步骤  早熟收敛机制
英文关键词  dolphin swarm algorithm  function optimization  length adaptive strategy  jumping steps  premature convergence mechanism
基金项目  国家自然科学基金,吉林省教育厅“十三五”科学技术研究, 吉林市科技创新发展 计划项目
学科分类代码  
作者单位E-mail
王艳娇 东北电力大学 wangyanjiao1028@126.com 
史新梦 东北电力大学  
中文摘要
      针对海豚群算法收敛速度慢、容易陷入局部最优等缺陷, 提出一种跳跃海豚群算法. 在搜寻阶段, 考虑进化时期对算法的影响, 对固定长度的声波参数实施自适应操作, 平衡算法的全局搜索和局部开发能力; 为加快算法的收敛速度, 在搜寻阶段之后加入跳跃步骤, 使个体直接跳到邻域最优解; 改进了捕猎阶段位置更新方式, 并加入变异扰动因子, 加快算法收敛速度的同时维持了种群的多样性; 为避免算法陷入局部最优, 在捕猎阶段后加入早熟收敛机制. 与6种进化算法在16个标准测试函数上进行测试, 结果表明, 本文算法较其他算法在收敛速度、收敛精度以及鲁棒性上优势明显.
英文摘要
      Jumping?Dolphin?Swarm?Algorithm(JDSA)?is?proposed?in?this?paper?to?improve?the?convergence?speed?of?Dolphin?Swarm?Algorithm(DSA)?and?prevent?it?from?falling?into?local?optimum.? Considering?the?influence?produced?by?different?periods?during?the?evolutionary?process,?adaptive?operations?are?added?to?fixed?length?acoustic?wave?parameters?in?the?search?phase,?which?balances?the?capabilities?of?global?search?and?local?development.The?jump?step?makes?the?individuals?jump?to?the?neighborhood?optimal?solution?directly?after?the?search?phase,?which?accelerates?the?convergence?speed?of?DSA.Besides,?the?updated?method?in?the?predation?stage?is?improved?and?the?variation?perturbation?factor?is?added?into?the?predation?stage,?which?improve?the?convergence?speed?as?well?as?maintain?the?diversity?of?the?population.In?order?to?prevent?the?algorithm?from?falling?into?local?optimum,?prematurity?convergence?mechanism?is?adopted?after?predation?stage.Compared?with?6?evolutionary?algorithms?on?19?standard?test?functions,?the?experimental?results?show?that?the?proposed?algorithm?has?obvious?advantages?on?convergence?speed,?convergence?accuracy?and?robustness.