"NSSMA算法的Matlab实现：多目标优化测试与案例分析，超体积度量与算法定制",非支配排序多目标黏菌优化算法(NSSMA) - Matlab实现 测试函数包括ZDT、DTLZ、WFG

jrjrGfVBxZIP非支配排序多目标黏.zip  112.24KB

资源文件列表:

ZIP 非支配排序多目标黏.zip 大约有13个文件
  1. 1.jpg 35.97KB
  2. 2.jpg 36.08KB
  3. 3.jpg 32.74KB
  4. 好的我将根据您提供的主题写一篇关于非支配.txt 1.75KB
  5. 非支配排序多目标黏菌优化算法及其在中的实现一.doc 2.23KB
  6. 非支配排序多目标黏菌优化算法实现测试.html 11.55KB
  7. 非支配排序多目标黏菌优化算法的实现.txt 1.96KB
  8. 非支配排序多目标黏菌优化算法的实现及.html 9.97KB
  9. 非支配排序多目标黏菌优化算法的实现及.txt 1.91KB
  10. 非支配排序多目标黏菌优化算法的实现及其.doc 1.84KB
  11. 非支配排序多目标黏菌优化算法的实现及其实验分.html 11.23KB
  12. 非支配排序多目标黏菌优化算法的实现及其实验测试一.txt 2.22KB
  13. 非支配排序多目标黏菌优化算法的实现及多目.txt 2.38KB

资源介绍:

"NSSMA算法的Matlab实现：多目标优化测试与案例分析，超体积度量与算法定制",非支配排序多目标黏菌优化算法(NSSMA) —— Matlab实现 测试函数包括ZDT、DTLZ、WFG、CF和UF共46个等，另外附有一个工程应用案例；评价指标包括超体积度量值HV、反向迭代距离IGD、迭代距离GD和空间评价SP等 可提供相关多目标算法定制、创新和改进多目标算法与预测算法结合程序定制，多目标优化等 代码质量极高，便于学习和理解 ,NSSMA; Matlab实现; 测试函数; 评价指标; 多目标算法定制; 算法创新; 程序定制; 优化算法; 代码质量高。,"多目标优化算法NSSMA的Matlab实现及工程应用案例"
<link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/css/base.min.css" rel="stylesheet"/><link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/css/fancy.min.css" rel="stylesheet"/><link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/90341922/2/raw.css" rel="stylesheet"/><div id="sidebar" style="display: none"><div id="outline"></div></div><div class="pf w0 h0" data-page-no="1" id="pf1"><div class="pc pc1 w0 h0"><img alt="" class="bi x0 y0 w1 h1" src="/image.php?url=https://csdnimg.cn/release/download_crawler_static/90341922/bg1.jpg"/><div class="t m0 x1 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">非支配排序多目标黏菌优化算法<span class="ff2">（<span class="ff3">NSSMA</span>）</span>及其在<span class="_ _0"> </span><span class="ff3">MATLAB<span class="_ _1"> </span></span>中的实现</div><div class="t m0 x1 h2 y2 ff1 fs0 fc0 sc0 ls0 ws0">一<span class="ff4">、</span>引言</div><div class="t m0 x1 h2 y3 ff1 fs0 fc0 sc0 ls0 ws0">随着优化问题日益复杂化<span class="ff2">，</span>多目标优化技术变得越来越重要<span class="ff4">。</span>非支配排序多目标黏菌优化算法<span class="ff2">（</span></div><div class="t m0 x1 h2 y4 ff3 fs0 fc0 sc0 ls0 ws0">NSSMA<span class="ff2">）<span class="ff1">作为一种高效的进化算法</span>，<span class="ff1">用于解决复杂的多目标优化问题<span class="ff4">。</span>本文将围绕该算法展开</span>，<span class="ff1">从</span></span></div><div class="t m0 x1 h2 y5 ff3 fs0 fc0 sc0 ls0 ws0">MATLAB<span class="_ _1"> </span><span class="ff1">实现到应用案例进行介绍<span class="ff2">，</span>并对相关的多目标算法的定制<span class="ff4">、</span>创新以及与其他算法的联合使用</span></div><div class="t m0 x1 h2 y6 ff1 fs0 fc0 sc0 ls0 ws0">做简要的说明<span class="ff4">。</span></div><div class="t m0 x1 h2 y7 ff1 fs0 fc0 sc0 ls0 ws0">二<span class="ff4">、</span>非支配排序多目标黏菌优化算法<span class="ff2">（<span class="ff3">NSSMA</span>）</span>简介</div><div class="t m0 x1 h2 y8 ff1 fs0 fc0 sc0 ls0 ws0">非支配排序多目标黏菌优化算法<span class="ff2">（<span class="ff3">NSSMA</span>）</span>是一种结合了多目标优化和黏菌优化思想的算法<span class="ff4">。</span>它通过</div><div class="t m0 x1 h2 y9 ff1 fs0 fc0 sc0 ls0 ws0">非支配排序和黏菌的觅食行为来寻找最优解集<span class="ff4">。</span>该算法具有全局搜索能力强<span class="ff4">、</span>收敛速度快等特点<span class="ff2">，</span>适</div><div class="t m0 x1 h2 ya ff1 fs0 fc0 sc0 ls0 ws0">用于处理复杂的非线性<span class="ff4">、</span>多目标优化问题<span class="ff4">。</span></div><div class="t m0 x1 h2 yb ff1 fs0 fc0 sc0 ls0 ws0">三<span class="ff4">、<span class="ff3">NSSMA<span class="_ _1"> </span></span></span>在<span class="_ _0"> </span><span class="ff3">MATLAB<span class="_ _1"> </span></span>中的实现</div><div class="t m0 x1 h2 yc ff1 fs0 fc0 sc0 ls0 ws0">在<span class="_ _0"> </span><span class="ff3">MATLAB<span class="_ _1"> </span></span>中实现<span class="_ _0"> </span><span class="ff3">NSSMA<span class="ff2">，</span></span>主要包括算法的流程设计<span class="ff4">、</span>参数设置<span class="ff4">、</span>测试函数的定义和评价指标的计算</div><div class="t m0 x1 h2 yd ff1 fs0 fc0 sc0 ls0 ws0">等<span class="ff4">。</span></div><div class="t m0 x1 h2 ye ff3 fs0 fc0 sc0 ls0 ws0">1.<span class="_ _2"> </span><span class="ff1">算法流程设计<span class="ff2">：</span>首先<span class="ff2">，</span>根据问题的特点设计算法的流程<span class="ff2">，</span>包括初始化种群<span class="ff4">、</span>非支配排序<span class="ff4">、</span>选择<span class="ff4">、</span></span></div><div class="t m0 x2 h2 yf ff1 fs0 fc0 sc0 ls0 ws0">交叉和变异等操作<span class="ff4">。</span></div><div class="t m0 x1 h2 y10 ff3 fs0 fc0 sc0 ls0 ws0">2.<span class="_ _2"> </span><span class="ff1">参数设置<span class="ff2">：</span>根据问题的规模和复杂度<span class="ff2">，</span>设置合适的参数<span class="ff2">，</span>如种群大小<span class="ff4">、</span>迭代次数<span class="ff4">、</span>交叉概率和变</span></div><div class="t m0 x2 h2 y11 ff1 fs0 fc0 sc0 ls0 ws0">异概率等<span class="ff4">。</span></div><div class="t m0 x1 h2 y12 ff3 fs0 fc0 sc0 ls0 ws0">3.<span class="_ _2"> </span><span class="ff1">测试函数定义<span class="ff2">：</span>根据需要选择合适的测试函数<span class="ff2">，</span>如<span class="_ _0"> </span></span>ZDT<span class="ff4">、</span>DTLZ<span class="ff4">、</span>WFG<span class="ff4">、</span>CF<span class="_ _1"> </span><span class="ff1">和<span class="_ _0"> </span></span>UF<span class="_ _1"> </span><span class="ff1">等<span class="ff2">，</span>用于评估</span></div><div class="t m0 x2 h2 y13 ff1 fs0 fc0 sc0 ls0 ws0">算法的性能<span class="ff4">。</span></div><div class="t m0 x1 h2 y14 ff3 fs0 fc0 sc0 ls0 ws0">4.<span class="_ _2"> </span><span class="ff1">评价指标计算<span class="ff2">：</span>计算超体积度量值<span class="_ _0"> </span></span>HV<span class="ff4">、<span class="ff1">反向迭代距离<span class="_ _0"> </span></span></span>IGD<span class="ff4">、<span class="ff1">迭代距离<span class="_ _0"> </span></span></span>GD<span class="_ _1"> </span><span class="ff1">和空间评价<span class="_ _0"> </span></span>SP<span class="_ _1"> </span><span class="ff1">等评价</span></div><div class="t m0 x2 h2 y15 ff1 fs0 fc0 sc0 ls0 ws0">指标<span class="ff2">，</span>用于评估算法的优化效果<span class="ff4">。</span></div><div class="t m0 x1 h2 y16 ff1 fs0 fc0 sc0 ls0 ws0">四<span class="ff4">、</span>测试函数与案例</div><div class="t m0 x1 h2 y17 ff3 fs0 fc0 sc0 ls0 ws0">1.<span class="_ _2"> </span><span class="ff1">测试函数<span class="ff2">：</span>包括<span class="_ _0"> </span></span>ZDT<span class="ff4">、</span>DTLZ<span class="ff4">、</span>WFG<span class="ff4">、</span>CF<span class="_ _1"> </span><span class="ff1">和<span class="_ _0"> </span></span>UF<span class="_ _1"> </span><span class="ff1">等<span class="_ _0"> </span></span>46<span class="_ _1"> </span><span class="ff1">个测试函数<span class="ff2">，</span>用于模拟各种复杂的优化问</span></div><div class="t m0 x2 h2 y18 ff1 fs0 fc0 sc0 ls0 ws0">题<span class="ff4">。</span></div><div class="t m0 x1 h2 y19 ff3 fs0 fc0 sc0 ls0 ws0">2.<span class="_ _2"> </span><span class="ff1">工程应用案例<span class="ff2">：</span>可以结合具体的工程问题<span class="ff2">，</span>如机械设计<span class="ff4">、</span>控制系统设计等<span class="ff2">，</span>将<span class="_ _0"> </span></span>NSSMA<span class="_ _1"> </span><span class="ff1">应用于实</span></div><div class="t m0 x2 h2 y1a ff1 fs0 fc0 sc0 ls0 ws0">际问题的求解中<span class="ff4">。</span></div><div class="t m0 x1 h2 y1b ff1 fs0 fc0 sc0 ls0 ws0">五<span class="ff4">、</span>多目标算法定制与创新</div></div><div class="pi" data-data='{"ctm":[1.568627,0.000000,0.000000,1.568627,0.000000,0.000000]}'></div></div>
100+评论
captcha
    相关资源