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<html xmlns="http://www.w3.org/1999/xhtml"> <head> <meta charset="utf-8"> <meta name="generator" content="pdf2htmlEX"> <meta http-equiv="X-UA-Compatible" content="IE=edge,chrome=1"> <link rel="stylesheet" href="https://static.pudn.com/base/css/base.min.css"> <link rel="stylesheet" href="https://static.pudn.com/base/css/fancy.min.css"> <link rel="stylesheet" href="https://static.pudn.com/prod/directory_preview_static/622b5fc03d2fbb0007cfe9e4/raw.css"> <script src="https://static.pudn.com/base/js/compatibility.min.js"></script> <script src="https://static.pudn.com/base/js/pdf2htmlEX.min.js"></script> <script> try{ pdf2htmlEX.defaultViewer = new pdf2htmlEX.Viewer({}); }catch(e){} </script> <title></title> </head> <body> <div id="sidebar" style="display: none"> <div id="outline"> </div> </div> <div id="pf1" class="pf w0 h0" data-page-no="1"><div class="pc pc1 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="https://static.pudn.com/prod/directory_preview_static/622b5fc03d2fbb0007cfe9e4/bg1.jpg"><div class="c x0 y1 w2 h2"><div class="t m0 x1 h3 y2 ff1 fs0 fc0 sc0 ls0 ws0">染整物流运输-库存成本最优化模型研究</div><div class="t m0 x2 h4 y3 ff1 fs1 fc0 sc1 ls0 ws0">阮学斌</div><div class="t m0 x3 h5 y4 ff3 fs2 fc0 sc1 ls0 ws0">1</div><div class="t m0 x4 h4 y3 ff3 fs1 fc0 sc1 ls0 ws0">,金福江</div><div class="t m0 x5 h5 y4 ff3 fs2 fc0 sc1 ls0 ws0">2</div><div class="t m0 x6 h6 y5 ff1 fs3 fc0 sc1 ls0 ws0">（1，福州大学自动化研究所，福建 福州 350001； </div><div class="t m0 x6 h6 y6 ff3 fs3 fc0 sc1 ls0 ws0">2，华侨大学信息科学与工程学院 福建 厦门 361021）</div><div class="t m0 x7 h7 y7 ff1 fs4 fc0 sc0 ls0 ws0">摘要：运输-库存联合模型及优化算法的研究对降低物流成本，提高企业经济效益具有重</div><div class="t m0 x7 h6 y8 ff1 fs3 fc0 sc1 ls0 ws0">要作用。本文通过对实际染整生产实际物流的深入分析，提出了将多供应方和多需求方之</div><div class="t m0 x7 h6 y9 ff1 fs3 fc0 sc1 ls0 ws0">间多种产品的运输和库存策略进行联合研究，建立了以总运输-库存成本最低为优化目标的</div><div class="t m0 x7 h6 ya ff1 fs3 fc0 sc1 ls0 ws0">运输-库存联合优化模型，根据该模型特点，设计了遗传算法求解出模型的最优解，最后通</div><div class="t m0 x7 h6 yb ff1 fs3 fc0 sc1 ls0 ws0">过实际染整企业的运输-库存实例说明了该模型的有效性和优越性。</div><div class="t m0 x7 h7 yc ff1 fs4 fc0 sc0 ls0 ws0">关键词：染整生产，物流，运输-库存模型，遗传算法</div><div class="t m0 x7 h8 yd ff6 fs0 fc0 sc1 ls0 ws0">Study on Transportation-Inventory Combination Model and</div><div class="t m0 x8 h8 ye ff6 fs0 fc0 sc1 ls0 ws0">Optimization Technology of Dyeing Production</div><div class="t m0 x9 h9 yf ff5 fs1 fc0 sc1 ls0 ws0">Ruan Xue-bin</div><div class="t m0 xa ha y10 ff5 fs2 fc0 sc1 ls0 ws0">1 </div><div class="t m0 xb h9 yf ff5 fs1 fc0 sc1 ls0 ws0">, Jin Fu-jiang</div><div class="t m0 xc ha y10 ff5 fs2 fc0 sc1 ls0 ws0">2</div><div class="t m0 xd hb y11 ff3 fs3 fc0 sc1 ls0 ws0">(1,the Automation Institute of Fuzhou University,FujianFuzhou 350001</div><div class="t m0 xe hc y12 ff3 fs3 fc0 sc1 ls0 ws0">2.Huaqiao University, College of Information Science & Engineering, Fujian</div><div class="t m0 xf hc y13 ff3 fs3 fc0 sc1 ls0 ws0">Xiamen, 361021)</div><div class="t m0 x7 h7 y14 ff6 fs4 fc0 sc1 ls0 ws0">Abstract：Study on transportation-inventory model and optimization algorithm plays</div><div class="t m0 x7 hd y15 ff5 fs4 fc0 sc1 ls0 ws0">an important role in reducing logistics cost and increasing enterprises economic</div><div class="t m0 x7 hd y16 ff5 fs4 fc0 sc1 ls0 ws0">benefit.This paper through the deep analysis of the actual dyeing production</div><div class="t m0 x7 hd y17 ff5 fs4 fc0 sc1 ls0 ws0">logistics,putting forward combining transportation and inventory which has multiple</div><div class="t m0 x7 hd y18 ff5 fs4 fc0 sc1 ls0 ws0">supply-sides,multiple products and multiple demand-sides, and establishing the</div><div class="t m0 x7 hd y19 ff5 fs4 fc0 sc1 ls0 ws0">transportation-inventory combination optimization model that put the much lower of</div><div class="t m0 x7 hd y1a ff5 fs4 fc0 sc1 ls0 ws0">total transportation fees and inventory fees as the optimization objection. Based on the</div><div class="t m0 x7 hd y1b ff5 fs4 fc0 sc1 ls0 ws0">characteristics of the model,the genetic algorithm is designed to solve the most</div><div class="t m0 x7 hd y1c ff5 fs4 fc0 sc1 ls0 ws0">optimal solution, finally, using the actual example of dyeing production to illustrate</div><div class="t m0 x7 hd y1d ff5 fs4 fc0 sc1 ls0 ws0">the validity and superiority of the model.</div><div class="t m0 x7 h7 y1e ff6 fs4 fc0 sc1 ls0 ws0">Key words:Dyeing production ， Logistics ， Transportation-inventory modeling ，</div><div class="t m0 x7 hd y1f ff5 fs4 fc0 sc1 ls0 ws0">Genetic algorithm. </div><div class="t m0 x10 h6 y20 ff1 fs3 fc0 sc1 ls0 ws0">单一的运输决策或库存控制问题的研究都各自取得了一些成就，但在新物流思潮下的</div><div class="t m0 x7 h6 y21 ff1 fs3 fc0 sc1 ls0 ws0">运输和库存决策的联合优化问题的研究才刚刚起步</div><div class="t m0 x11 he y22 ff5 fs5 fc0 sc1 ls0 ws0">[1]</div><div class="t m0 x12 h6 y21 ff1 fs3 fc0 sc1 ls0 ws0">，Federgruen</div><div class="t m0 x13 he y22 ff5 fs5 fc0 sc1 ls0 ws0">[2]</div><div class="t m0 x14 h6 y21 ff1 fs3 fc0 sc1 ls0 ws0">首次把库存与运输问题</div><div class="t m0 x7 h6 y23 ff1 fs3 fc0 sc1 ls0 ws0">整合优化。目前，全球市场竞争力的不断加剧，促使了配送一体化的高效益和高效率的模</div><div class="t m0 x7 h6 y24 ff1 fs3 fc0 sc1 ls0 ws0">式逐渐显现其重要性，而运输和库存控制的联合优化问题也逐渐成为学者们研究的重点</div><div class="t m0 x7 he y25 ff5 fs5 fc0 sc1 ls0 ws0">[3]</div><div class="t m0 x15 h6 y26 ff1 fs3 fc0 sc1 ls0 ws0">，在诸多学者对于库存运输两大系统整合在一起进行了研究</div><div class="t m0 x16 he y25 ff5 fs5 fc0 sc1 ls0 ws0">[4-8]</div><div class="t m0 x17 h6 y26 ff1 fs3 fc0 sc1 ls0 ws0">。在企业物流管理系统中，</div><div class="t m0 x7 h6 y27 ff1 fs3 fc0 sc1 ls0 ws0">由于运输和库存的控制问题存在着利益相背的关系，这使得对他们的联合优化控制的研究</div><div class="t m0 x7 h6 y28 ff1 fs3 fc0 sc1 ls0 ws0">更为重要</div><div class="t m0 x18 he y29 ff5 fs5 fc0 sc1 ls0 ws0">[9]</div><div class="t m0 x19 h6 y28 ff1 fs3 fc0 sc1 ls0 ws0">。因此，探求一个企业产品运输和库存的联合优化模型，不仅可以降低企业的</div><div class="t m0 x7 h6 y2a ff1 fs3 fc0 sc1 ls0 ws0">物流成本，提高企业的经济效益和管理技术水平，还可以为企业的物流决策管理提供指导</div><div class="t m0 x7 h6 y2b ff1 fs3 fc0 sc1 ls0 ws0">作用。近几年，对于运输与库存整合模型有了新的研究，如韩伟博士</div><div class="t m0 x1a he y2c ff5 fs5 fc0 sc1 ls0 ws0">[10]</div><div class="t m0 x1b h6 y2b ff1 fs3 fc0 sc1 ls0 ws0">提出的基于了基于</div></div></div><div class="pi" data-data='{"ctm":[1.611850,0.000000,0.000000,1.611850,0.000000,0.000000]}'></div></div> </body> </html>

<div id="pf2" class="pf w0 h0" data-page-no="2"><div class="pc pc2 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="https://static.pudn.com/prod/directory_preview_static/622b5fc03d2fbb0007cfe9e4/bg2.jpg"><div class="c x0 y1 w2 h2"><div class="t m0 x7 h6 y2d ff1 fs3 fc0 sc1 ls0 ws0">作业整合的运输与库存联合优化；肖继先</div><div class="t m0 x1c he y2e ff5 fs5 fc0 sc1 ls0 ws0">[11]</div><div class="t m0 x1d h6 y2d ff1 fs3 fc0 sc1 ls0 ws0">从最大最小运送周期的角度研究库存与运输模</div><div class="t m0 x7 h6 y2f ff1 fs3 fc0 sc1 ls0 ws0">型。虽然针对库存和运输模型提出的新的方法。但其研究的角度是单一物品的价格、周期</div><div class="t m0 x7 h6 y30 ff1 fs3 fc0 sc1 ls0 ws0">等因素，而本文对于的对象是多个物品、多个供应方、多个需求方之间的库存—运输模型。</div><div class="t m0 x10 h6 y31 ff1 fs3 fc0 sc1 ls0 ws0">本文通过对实际染整生产物流调度特点的深入分析，提出了将多供应方和多需求方之</div><div class="t m0 x7 h6 y32 ff1 fs3 fc0 sc1 ls0 ws0">间多种产品的运输策略和库存策略进行联合研究，并根据实际染整生产的运输和库存控制</div><div class="t m0 x7 h6 y33 ff1 fs3 fc0 sc1 ls0 ws0">的联合特性建立了以总运输-库存成本最低为优化目标，以供应能力、总需求量、初始库存</div><div class="t m0 x7 h6 y34 ff1 fs3 fc0 sc1 ls0 ws0">量、安全库存量等为约束条件的运输-库存联合优化模型，并设计遗传算法求解出模型的最</div><div class="t m0 x7 h6 y35 ff1 fs3 fc0 sc1 ls0 ws0">优调度方案，即产品的最优订货策略和需求方的最佳库存需求量，最后通过实际染整生产</div><div class="t m0 x7 h6 y36 ff1 fs3 fc0 sc1 ls0 ws0">的运输-库存实例说明模型的有效性和优越性。</div><div class="t m0 x7 h4 y37 ff3 fs1 fc0 sc1 ls0 ws0">1 染整生产运输-库存联合优化模型</div><div class="t m0 x7 h7 y38 ff5 fs4 fc0 sc1 ls0 ws0">1.1 目标函数</div><div class="t m0 x10 h6 y39 ff1 fs3 fc0 sc1 ls0 ws0">本文根据实际染整生产的运输和库存的联合特性建立以订购费用、存储费用和运输费</div><div class="t m0 x7 h6 y3a ff1 fs3 fc0 sc1 ls0 ws0">用之和费用最低为优化目标的染整生产运输-库存联合优化模型。</div><div class="t m0 x10 h6 y3b ff1 fs3 fc0 sc1 ls0 ws0">运输-库存联合优化模型基于如下假设：①所有需求点都由一个人集中管理，供应方不</div><div class="t m0 x7 h6 y3c ff7 fs3 fc0 sc1 ls0 ws0">保有库存；②不允许缺货；③各个需求点间的需求是相互独立、均匀的，所有需求点中各</div><div class="t m0 x7 h6 y3d ff1 fs3 fc0 sc1 ls0 ws0">种物品的需求量之和是确定的。</div><div class="t m0 x10 h6 y3e ff1 fs3 fc0 sc1 ls0 ws0">设有 种产品 ；由 个供应方 进行供应，各供应方的</div><div class="t m0 x7 h6 y3f ff1 fs3 fc0 sc1 ls0 ws0">供应量分别为 ；所有供应方供应的产品全部运往 个需求方 ，</div><div class="t m0 x7 h6 y40 ff1 fs3 fc0 sc1 ls0 ws0">各需求方的初始库存量分别为 ，安全库存量分别为 。</div><div class="t m0 x10 h6 y41 ff1 fs3 fc0 sc1 ls0 ws0">设 为供应方 向需求方 运输第 种产品的单</div><div class="t m0 x7 h6 y42 ff7 fs3 fc0 sc1 ls0 ws0">位运输费用； 为需求方 从供应方 处订购第 种</div><div class="t m0 x7 h6 y43 ff1 fs3 fc0 sc1 ls0 ws0">产 品 的 单 位 订 购 费 用 ； 为 供 应 方 向 需 求 方 运 输 第</div><div class="t m0 x1e h6 y44 ff1 fs3 fc0 sc1 ls0 ws0">种产品的运输量；</div><div class="t m0 x1f h6 y45 ff1 fs3 fc0 sc1 ls0 ws0">运输费用为单位运价与产品货运量之积，订购费用为单位订购费与产品货运量之</div><div class="t m0 x7 h6 y46 ff7 fs3 fc0 sc1 ls0 ws0">积，即将上述单位运费矩阵、单位订购费用矩阵分别与产品货运量矩阵进行点乘及求</div><div class="t m0 x7 h6 y47 ff1 fs3 fc0 sc1 ls0 ws0">和运算，就得出染整生产运输和库存联合优化模型的总运输费用：</div><div class="t m0 x20 h6 y48 ff5 fs3 fc0 sc1 ls0 ws0"> （1）</div><div class="t m0 xd h6 y49 ff1 fs3 fc0 sc1 ls0 ws0">总订购费用：</div></div></div><div class="pi" data-data='{"ctm":[1.611850,0.000000,0.000000,1.611850,0.000000,0.000000]}'></div></div>