Matlab 车辆配送路径规划问题四大算法解决旅行商问题(TSP) CVRP CDVRP VRPTWtsp:旅行商问题，寻

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ZIP 车辆配送路径规划问题四大算法解决旅行商问题.zip 大约有15个文件
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  8. 标题车辆配送路径规划问题四大算法解决旅行.doc 2.4KB
  9. 车辆配送路径规划技术分析文章一引言在物流和运输领域.txt 3.3KB
  10. 车辆配送路径规划深入探讨旅行商.txt 2.83KB
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  13. 车辆配送路径规划问题在现代物流配送领域.txt 2.12KB
  14. 车辆配送路径规划问题解析四大算法解.txt 2.62KB
  15. 车辆配送路径规划问题随着物流行业的不断发展如何高.txt 1.84KB

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Matlab 车辆配送路径规划问题 四大算法解决旅行商问题(TSP) CVRP CDVRP VRPTW tsp:旅行商问题，寻找最短闭合路径 cvrp:带容量约束的车辆路径规划 dvrp:带距离约束的车辆路径规划 cdvrp:带距离+容量约束的车辆路径规划 vrptw：带距离+容量+时间窗约束的车辆路径规划 源码+详细注释 坐标需求量载重量等数据可以更改
<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/89763000/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/89763000/bg1.jpg"/><div class="t m0 x1 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">标题<span class="ff2">：<span class="ff3">Matlab<span class="_ _0"> </span></span></span>车辆配送路径规划问题<span class="ff2">：</span>四大算法解决旅行商问题及其变种</div><div class="t m0 x1 h2 y2 ff1 fs0 fc0 sc0 ls0 ws0">摘要<span class="ff2">：</span></div><div class="t m0 x1 h2 y3 ff1 fs0 fc0 sc0 ls0 ws0">本文将介绍在<span class="_ _1"> </span><span class="ff3">Matlab<span class="_ _0"> </span></span>环境下<span class="ff2">，</span>使用四大算法解决车辆配送路径规划问题<span class="ff2">（<span class="ff3">TSP</span>）</span>及其变种<span class="ff2">，</span>包括带</div><div class="t m0 x1 h2 y4 ff1 fs0 fc0 sc0 ls0 ws0">容量约束的车辆路径规划<span class="ff2">（<span class="ff3">CVRP</span>）<span class="ff4">、</span></span>带距离约束的车辆路径规划<span class="ff2">（<span class="ff3">DVRP</span>）<span class="ff4">、</span></span>带距离<span class="ff3">+</span>容量约束的车辆</div><div class="t m0 x1 h2 y5 ff1 fs0 fc0 sc0 ls0 ws0">路径规划<span class="ff2">（<span class="ff3">CDVRP</span>）</span>以及带距离<span class="ff3">+</span>容量<span class="ff3">+</span>时间窗约束的车辆路径规划<span class="ff2">（<span class="ff3">VRPTW</span>）<span class="ff4">。</span></span>本文提供了详细的源</div><div class="t m0 x1 h2 y6 ff1 fs0 fc0 sc0 ls0 ws0">码和注释<span class="ff2">，</span>并可根据需求更改坐标<span class="ff4">、</span>需求量<span class="ff4">、</span>载重量等数据<span class="ff4">。</span></div><div class="t m0 x1 h2 y7 ff1 fs0 fc0 sc0 ls0 ws0">第一章<span class="ff2">：</span>引言</div><div class="t m0 x1 h2 y8 ff3 fs0 fc0 sc0 ls0 ws0">1.1 <span class="ff1">背景</span></div><div class="t m0 x1 h2 y9 ff1 fs0 fc0 sc0 ls0 ws0">车辆配送路径规划问题是在实际物流配送中常遇到的难题之一<span class="ff4">。</span>解决这一问题可以有效提高配送效率</div><div class="t m0 x1 h2 ya ff4 fs0 fc0 sc0 ls0 ws0">、<span class="ff1">降低成本<span class="ff2">，</span>并优化客户满意度</span>。</div><div class="t m0 x1 h2 yb ff3 fs0 fc0 sc0 ls0 ws0">1.2 <span class="ff1">目的</span></div><div class="t m0 x1 h2 yc ff1 fs0 fc0 sc0 ls0 ws0">本文旨在介绍<span class="_ _1"> </span><span class="ff3">Matlab<span class="_ _0"> </span></span>环境下应用四大算法解决旅行商问题及其变种<span class="ff2">，</span>为物流从业者提供实用的解决</div><div class="t m0 x1 h2 yd ff1 fs0 fc0 sc0 ls0 ws0">方案<span class="ff4">。</span></div><div class="t m0 x1 h2 ye ff1 fs0 fc0 sc0 ls0 ws0">第二章<span class="ff2">：</span>旅行商问题<span class="ff2">（<span class="ff3">TSP</span>）</span></div><div class="t m0 x1 h2 yf ff3 fs0 fc0 sc0 ls0 ws0">2.1 <span class="ff1">定义</span></div><div class="t m0 x1 h2 y10 ff1 fs0 fc0 sc0 ls0 ws0">旅行商问题是指在给定城市之间的距离矩阵下<span class="ff2">，</span>寻找一条路径<span class="ff2">，</span>使得旅行商能够从起始城市出发<span class="ff2">，</span>经</div><div class="t m0 x1 h2 y11 ff1 fs0 fc0 sc0 ls0 ws0">过其他城市<span class="ff2">，</span>最终回到起始城市<span class="ff2">，</span>并使得路径总长度最短<span class="ff4">。</span></div><div class="t m0 x1 h2 y12 ff3 fs0 fc0 sc0 ls0 ws0">2.2 TSP<span class="_ _0"> </span><span class="ff1">的解决方法</span></div><div class="t m0 x1 h2 y13 ff1 fs0 fc0 sc0 ls0 ws0">本节介绍了四大经典算法<span class="ff2">（</span>贪心算法<span class="ff4">、</span>回溯算法<span class="ff4">、</span>动态规划算法<span class="ff4">、</span>遗传算法<span class="ff2">）</span>在解决<span class="_ _1"> </span><span class="ff3">TSP<span class="_ _0"> </span></span>问题中的应</div><div class="t m0 x1 h2 y14 ff1 fs0 fc0 sc0 ls0 ws0">用<span class="ff2">，</span>并提供了相应的源码和详细注释<span class="ff4">。</span></div><div class="t m0 x1 h2 y15 ff1 fs0 fc0 sc0 ls0 ws0">第三章<span class="ff2">：</span>带容量约束的车辆路径规划<span class="ff2">（<span class="ff3">CVRP</span>）</span></div><div class="t m0 x1 h2 y16 ff3 fs0 fc0 sc0 ls0 ws0">3.1 <span class="ff1">定义</span></div><div class="t m0 x1 h2 y17 ff3 fs0 fc0 sc0 ls0 ws0">CVRP<span class="_ _0"> </span><span class="ff1">是在<span class="_ _1"> </span></span>TSP<span class="_ _0"> </span><span class="ff1">的基础上增加了车辆的容量约束<span class="ff2">，</span>即每个城市对应的需求量不得超过车辆的装载量<span class="ff4">。</span></span></div><div class="t m0 x1 h2 y18 ff3 fs0 fc0 sc0 ls0 ws0">3.2 CVRP<span class="_ _0"> </span><span class="ff1">的解决方法</span></div><div class="t m0 x1 h2 y19 ff1 fs0 fc0 sc0 ls0 ws0">本节介绍了四大算法在解决<span class="_ _1"> </span><span class="ff3">CVRP<span class="_ _0"> </span></span>问题中的应用<span class="ff2">，</span>并提供了相应的源码和详细注释<span class="ff4">。</span></div><div class="t m0 x1 h2 y1a ff1 fs0 fc0 sc0 ls0 ws0">第四章<span class="ff2">：</span>带距离约束的车辆路径规划<span class="ff2">（<span class="ff3">DVRP</span>）</span></div><div class="t m0 x1 h2 y1b ff3 fs0 fc0 sc0 ls0 ws0">4.1 <span class="ff1">定义</span></div><div class="t m0 x1 h2 y1c ff3 fs0 fc0 sc0 ls0 ws0">DVRP<span class="_ _0"> </span><span class="ff1">是在<span class="_ _1"> </span></span>TSP<span class="_ _0"> </span><span class="ff1">的基础上增加了车辆的距离约束<span class="ff2">，</span>即每个城市之间的距离不得超过车辆的行驶能力<span class="ff4">。</span></span></div><div class="t m0 x1 h2 y1d ff3 fs0 fc0 sc0 ls0 ws0">4.2 DVRP<span class="_ _0"> </span><span class="ff1">的解决方法</span></div></div><div class="pi" data-data='{"ctm":[1.568627,0.000000,0.000000,1.568627,0.000000,0.000000]}'></div></div>
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