<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article  PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article"><front><journal-meta><journal-id journal-id-type="publisher-id">JCC</journal-id><journal-title-group><journal-title>Journal of Computer and Communications</journal-title></journal-title-group><issn pub-type="epub">2327-5219</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/jcc.2014.25002</article-id><article-id pub-id-type="publisher-id">JCC-44187</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Computer Science&amp;Communications</subject></subj-group></article-categories><title-group><article-title>
 
 
  The Research of Terminal Distribution Network Path Optimization
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>ufeng</surname><given-names>Zhang</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Xinyu</surname><given-names>Zhang</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib></contrib-group><aff id="aff2"><addr-line>Graduate College, Beijing Wuzi University, Beijing, China</addr-line></aff><aff id="aff1"><addr-line>International College, Beijing Wuzi University, Beijing, China</addr-line></aff><author-notes><corresp id="cor1">* E-mail:<email>xinyu715@126.com(XZ)</email>;</corresp></author-notes><pub-date pub-type="epub"><day>25</day><month>03</month><year>2014</year></pub-date><volume>02</volume><issue>05</issue><fpage>28</fpage><lpage>37</lpage><history><date date-type="received"><day>27</day>	<month>December</month>	<year>2013</year></date><date date-type="rev-recd"><day>25</day>	<month>January</month>	<year>2014</year>	</date><date date-type="accepted"><day>3</day>	<month>February</month>	<year>2014</year></date></history><permissions><copyright-statement>&#169; Copyright  2014 by authors and Scientific Research Publishing Inc. </copyright-statement><copyright-year>2014</copyright-year><license><license-p>This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/</license-p></license></permissions><abstract><p>
 
 
   This paper presents an optimization problem about terminal distribution network path, defining the research problem through its distribution operation process, next to the terminal distribution route optimization. To begin with, dynamic optimization algorithm is built, the first from the target distribution node distribution vehicle, and goods to N customers are delivered, in the most appropriate distribution route to the minimum distribution distance and optimizing the terminal distribution path. Two parts to build and example areincluding algorithm. 
 
</p></abstract><kwd-group><kwd>The Terminal Distribution; Dynamic Optimization Algorithm; Path Optimization</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>In the process of logistic distribution network optimization, two stages are included: the first stage is the path optimization of distribution between nodes, namely the goods in the process of continuous distribution, the path between source node distribution to the target distribution optimization process; the second stage is the terminal distribution route optimization, namely by the target distribution node to the path optimization process between multiple clients. So this article mainly aims at terminal distribution route optimization problem. The terminal distribution route optimization is in the process of building dynamic optimization algorithm, from the target distribution node distribution vehicle, and delivering goods to N customers, in the most appropriate distribution route to the minimum distribution distance and optimizing the terminal distribution path.</p></sec><sec id="s2"><title>2. Research Overview of the Logistics Distribution Network Path Optimization Problem</title><sec id="s2_1"><title>2.1. Distribution Network Path Optimization Research</title><p>Path optimization problem in logistics distribution network with the traditional path optimization problem has certain difference, path optimization problems in network aiming at the condition of the traverse network point or edge can be divided into arc routing problem and point path problem. Among them, the arc routing problem consider is to service in the network edge, and some path problem is main consideration of neutral network service. A typical representative of the typical point path is traveling salesman problem and vehicle routing problem.</p><p>In view of the distribution network and its path optimization, Niu Yongliang [<xref ref-type="bibr" rid="scirp.44187-ref1">1</xref>] proposed a “three level” such as logistics distribution network structure, this structure with conform to the actual network structure of enterprise, on the principle of “quadtree” partition to the customer, using a two-phase heuristic algorithm to optimize the vehicle driving route. Wang Rumei [<xref ref-type="bibr" rid="scirp.44187-ref2">2</xref>] , such as the freedom of the traditional annealing algorithm into directional annealing algorithm, and the examples show that this algorithm improves the efficiency. Jiang Zhongzhong [<xref ref-type="bibr" rid="scirp.44187-ref3">3</xref>] , in the research of vehicle routing optimization problem, starting from the actual situation in the process of delivery, considering the uncertainty of vehicle travel time and customer service time, the logistics distribution network composed of distribution center and customer two kinds of nodes is not completely undirected graph representation, established a fuzzy programming model of logistics distribution vehicle routing optimization. Liu Qiusheng [<xref ref-type="bibr" rid="scirp.44187-ref4">4</xref>] , such as vehicle loading optimization model is established, using the dynamic programming method to obtain the optimal solution.</p><p>Ko Hyun-Jeung and Geraldw. Evans (2007) [<xref ref-type="bibr" rid="scirp.44187-ref5">5</xref>] from the perspective of third-party logistics enterprises to build and optimize the mixed integer nonlinear programming model of reverse logistics, and puts forward the genetic algorithm based on heuristic algorithm to solve the model, Ma Zujun [<xref ref-type="bibr" rid="scirp.44187-ref6">6</xref>] from the Angle of the operating cost minimum, establishes the mixed integer linear programming model, in order to determine the number of facilities, location, and every reasonable logistics path through put.</p><p>H. A. Eliselt [<xref ref-type="bibr" rid="scirp.44187-ref7">7</xref>] mainly explores several categories such as: Chinese postman algorithm to the Chinese postal problems, have no to China post road, windy China postal problems, mixed China post road, heuristic China postal problems. G. Groves [<xref ref-type="bibr" rid="scirp.44187-ref8">8</xref>] study the profit maximization of China post road. W. L. Pharn [<xref ref-type="bibr" rid="scirp.44187-ref9">9</xref>] in combination with a variety of graph theory algorithm, at the same time considering the vehicle routing and scheduling management two aspects of the path optimization problem. Qin Wenqing [<xref ref-type="bibr" rid="scirp.44187-ref10">10</xref>] , from the cooperation of supply chain level (horizontal), optimizes distribution network. The purpose is to improve the whole service level of the supply chain logistics network.</p></sec><sec id="s2_2"><title>2.2. Literature Review</title><p>Most scholars in the research question will focus on the algorithm was improved, and focused on the goal of optimization design, but most of the studies did not fully combined with the actual distribution of the characteristics of the transportation network, most researchers think in between any two points can be directly to the model and algorithm on the basis of the design, so the logistics distribution route optimization problem with distribution of transportation network connectivity, remains to be further studied.</p><p>In most of these studies focused on the path of the logistics distribution network under normal conditions for optimization problems, due to the logistics distribution network not only include the traditional “positive” logistics distribution network, at the same time also includes return and old product recycling in the reuse of reverse logistics network, so in view of the combination of forward and reverse logistics distribution network in the path optimization problem remains to be further discussed.</p></sec><sec id="s2_3"><title>2.3. Research Purposes</title><p>In view of the different nature and function of logistics distribution network nodes, the phases to solve the problem of logistics distribution network path optimization ideas and methods.</p><p>In logistics distribution network structure and based on the operation process of logistics distribution network, on the basis of logistics enterprises in the operating process of the path optimization of logistics distribution network can be divided into different stages. According to the characteristics of the second phase terminal distribution route optimization, constructing closed-loop dynamic optimization algorithm, and validate through the case.</p></sec></sec><sec id="s3"><title>3. The Terminal Distribution Operation Process Ease</title><p>1) Distribution location of dispatching personnel according to the customer, to customer order classification, divided into basic distribution area.</p><p>2) The nature of the goods, goods dispatching personnel according to user’s need to classify the goods, will be the similar goods together, complete vehicle loading.</p><p>3) According to the required time to the customer order, determine the order of distribution, order of the identified here is tentative, because the further optimization needs according to the specific situation.</p><p>4) Operator according to the situation of the goods, the cost to arrange vehicles, according to the actual situation to choose outsourcing transportation or their own transport.</p><p>5) The operator according to the customer’s position, the time of delivery requirements and local traffic condition, to determine the distribution line, as far as possible to meet customer request at the same time, the lowest transportation cost.</p><p>6) Determine after distribution line, according to the principle of minimum saving mileage, can determine the distribution order.</p><p>7) On the basis of certain distribution order, send before they are installed, after send first loading principle, loading, then transportation [<xref ref-type="bibr" rid="scirp.44187-ref11">11</xref>] .</p><p>8) The customer sign for it, the owner customer and salesman, has its own team or other service providers to point the goods after the sign or seal on the delivery form, by a solicitor, has its own team or other service providers will bring the relevant papers and documents back. Distribution stage at the end of the operation flow chart shown in figure 1.</p><p>From the point of view of the operation process of distribution between nodes, the key lies in the order in the shipping transit transfer process between the nodes, so in different constant goods distribution, the distribution of nodes by the source of goods distribution node to the target distribution by repeated movement-pause-sportspause. Through the analysis of enterprise logistics distribution system, can pause in the abstract into node, movement can be abstract as chain. Such goods distribution can be defined as the goods between distribution node in network of nodes and lines that connect the direction of the movement in the transfer process. From the operation process of the end of delivery, the key point is that the goods allocation process between customers, that is, from a process of distribution network at the grass-roots level to multiple clients. Because of the node of the two phase involves different, operation process is also different, so the path of the distribution network optimization problem was divided into different stages [<xref ref-type="bibr" rid="scirp.44187-ref12">12</xref>] .</p></sec><sec id="s4"><title>4. Terminal Distribution Path Optimization Research</title><sec id="s4_1"><title>4.1. The Terminal Distribution Route Optimization Task Model</title><p>The terminal distribution of the path optimization of logistics distribution network is goods from grassroots target distribution path optimization process between the node to multiple clients. The problem set from a primary distribution node from the system (1) is assumed to be node sends a vehicle to each customer within the system for material distribution, distribution again after the completion of the each customer returns and recycling materials back to the primary distribution node 1. Research on material distribution vehicle shortest path and route. So it is a combination of forward logistics and reverse logistics of closed-loop path on closed-loop logistics network optimization process, as shown in figure 1. Lines represent different nodes in the network transport of goods between the moving route, there may be multiple transport routes between any pair of nodes are linked together, these lines represent the different mode of transportation, transportation routes or different goods.</p><p>Mentioned in this paper, the closed-loop logistics refers to the full consideration in the process of traditional logistics distribution in reverse logistics, and put forward logistics and reverse logistics distribution system analysis and processing, make the logistics distribution system more reasonable, it is in the reverse logistics and forward logistics distribution is put forward on the basis of the combination of. As a result, the composition of closed-loop logistics network should include the following two parts: traditional “positive” logistics distribution</p></sec></sec></body><back><ref-list><title>References</title><ref id="scirp.44187-ref1"><label>1</label><mixed-citation publication-type="journal" xlink:type="simple"><name name-style="western"><surname>Niu</surname><given-names> Y.L. and Wang</given-names></name>,<name name-style="western"><surname> J.M. </surname><given-names>  </given-names></name>,<etal>et al</etal>. (<year>2006</year>)<article-title>Logistics Distribution Vehicle Route Algorithm</article-title><source> Journal of Transportation Engineering</source><volume> 6</volume>,<fpage> 83</fpage>-<lpage>87</lpage>.<pub-id pub-id-type="doi"></pub-id></mixed-citation></ref><ref id="scirp.44187-ref2"><label>2</label><mixed-citation publication-type="journal" xlink:type="simple"><name name-style="western"><surname>Wang</surname><given-names> R.M.</given-names></name>,<name name-style="western"><surname> Wang</surname><given-names> S.M. and Wang</given-names></name>,<name name-style="western"><surname> Z.J. </surname><given-names>  </given-names></name>,<etal>et al</etal>. (<year>2007</year>)<article-title>Directional Simulated Annealing Algorithm Is a Kind of Vehicle Routing Problem</article-title><source> Manufacturing Technology Research</source><volume> 1</volume>,<fpage> 16</fpage>-<lpage>19</lpage>.<pub-id pub-id-type="doi"></pub-id></mixed-citation></ref><ref id="scirp.44187-ref3"><label>3</label><mixed-citation publication-type="journal" xlink:type="simple"><name name-style="western"><surname>Jiang</surname><given-names> Z.Z. and Wang</given-names></name>,<name name-style="western"><surname> D.W. </surname><given-names>  </given-names></name>,<etal>et al</etal>. (<year>2006</year>)<article-title>And Fuzzy Planning Model of Logistics Distribution Vehicle Routing Optimization Algorithm</article-title><source> Journal of System Simulation</source><volume> 17</volume>,<fpage> 3301</fpage>-<lpage>3304</lpage>.<pub-id pub-id-type="doi"></pub-id></mixed-citation></ref><ref id="scirp.44187-ref4"><label>4</label><mixed-citation publication-type="journal" xlink:type="simple"><name name-style="western"><surname>Liu</surname><given-names> Q.S.</given-names></name>,<name name-style="western"><surname> Wen</surname><given-names> X.J. and Pan</given-names></name>,<name name-style="western"><surname> X.X. </surname><given-names>  </given-names></name>,<etal>et al</etal>. (<year>2009</year>)<article-title>Home Appliances to the Countryside in the Logistics Distribution System Optimization of Vehicle Loading Study</article-title><source> Commercial Modernization</source><volume> 575</volume>,<fpage> 119</fpage>-<lpage>120</lpage>.<pub-id pub-id-type="doi"></pub-id></mixed-citation></ref><ref id="scirp.44187-ref5"><label>5</label><mixed-citation publication-type="other" xlink:type="simple">Hyun, J.K. and Gerald, W.E. (2007) A Genetic Algorithm-Based Heuristic for the Dynamic Integrated forward/ Reverse Logistics Network for 3PLs. Computers &amp; Operations Research, 34, 346-366. 
http://dx.doi.org/10.1016/j.cor.2005.03.004</mixed-citation></ref><ref id="scirp.44187-ref6"><label>6</label><mixed-citation publication-type="journal" xlink:type="simple"><name name-style="western"><surname>Ma</surname><given-names> Z.J. </given-names></name>,<etal>et al</etal>. (<year>2005</year>)<article-title>Generation of Clever. Products Recycling Reverse Logistics Network Optimization Design Model</article-title><source> Journal of Management Engineering</source><volume> 12</volume>,<fpage> 114</fpage>-<lpage>117</lpage>.<pub-id pub-id-type="doi"></pub-id></mixed-citation></ref><ref id="scirp.44187-ref7"><label>7</label><mixed-citation publication-type="other" xlink:type="simple">Eiselt, H.A., Michel, G. and Gilbert, L. (1995) Arc Routing Problems, Part I: The Chinese Postman Problem. Operations Research, 43, 231-242. http://dx.doi.org/10.1287/opre.43.2.231</mixed-citation></ref><ref id="scirp.44187-ref8"><label>8</label><mixed-citation publication-type="journal" xlink:type="simple"><name name-style="western"><surname>Groves</surname><given-names> G.</given-names></name>,<name name-style="western"><surname> le Roux</surname><given-names> J. and van Vuuren</given-names></name>,<name name-style="western"><surname> J.H. </surname><given-names>  </given-names></name>,<etal>et al</etal>. (<year>2004</year>)<article-title>Network Service Scheduling and Routing</article-title><source> International Transactions in Operational</source><volume> 11</volume>,<fpage> 613</fpage>-<lpage>643</lpage>.<pub-id pub-id-type="doi"></pub-id></mixed-citation></ref><ref id="scirp.44187-ref9"><label>9</label><mixed-citation publication-type="other" xlink:type="simple">Pharn, W.L. and Chiu, W.C. (2005) Approximate Solutions for the Maximum Benefit Chinese Postman Problem. International Journal of Systems Science, 36, 815-822. http://dx.doi.org/10.1080/0020 7720500282292</mixed-citation></ref><ref id="scirp.44187-ref10"><label>10</label><mixed-citation publication-type="other" xlink:type="simple">Qin, W.Q. (2006) Horizontal Cooperation Supply Chain and Distribution Network Research. Guangxi University.</mixed-citation></ref><ref id="scirp.44187-ref11"><label>11</label><mixed-citation publication-type="journal" xlink:type="simple"><name name-style="western"><surname>Mou</surname><given-names> L.M. and Dai</given-names></name>,<name name-style="western"><surname> X.D. </surname><given-names>  </given-names></name>,<etal>et al</etal>. (<year>2013</year>)<article-title>Effective in Solving Selective Single Commodity Distribution Collection of Ant Colony Algorithm</article-title><source> Journal of Computer Applications and Software</source><volume> 30</volume>,<fpage> 93</fpage>-<lpage>96</lpage>.<pub-id pub-id-type="doi"></pub-id></mixed-citation></ref><ref id="scirp.44187-ref12"><label>12</label><mixed-citation publication-type="journal" xlink:type="simple"><name name-style="western"><surname>Zhou</surname><given-names> Y.C. and Sun</given-names></name>,<name name-style="western"><surname> X.C. </surname><given-names>  </given-names></name>,<etal>et al</etal>. (<year>2012</year>)<article-title>Logistics Distribution Path Optimization Research Based on Improved Genetic Algorithm</article-title><source> Computer Engineering and Science</source><volume> 10</volume>,<fpage> 118</fpage>-<lpage>122</lpage>.<pub-id pub-id-type="doi"></pub-id></mixed-citation></ref><ref id="scirp.44187-ref13"><label>13</label><mixed-citation publication-type="journal" xlink:type="simple"><name name-style="western"><surname>Long</surname><given-names> H. and Wu</given-names></name>,<name name-style="western"><surname> Y. </surname><given-names>  </given-names></name>,<etal>et al</etal>. (<year>2012</year>)<article-title>Time-Varying under the Condition of City Logistics Distribution Vehicle Routing Optimization</article-title><source> Journal of Automobile Industry of Hubei Province College</source><volume> 2</volume>,<fpage> 42</fpage>-<lpage>45</lpage>.<pub-id pub-id-type="doi"></pub-id></mixed-citation></ref><ref id="scirp.44187-ref14"><label>14</label><mixed-citation publication-type="journal" xlink:type="simple"><name name-style="western"><surname>Wang</surname><given-names> N.L. </given-names></name>,<etal>et al</etal>. (<year>2012</year>)<article-title>The Automobile Assembly Line Material Distribution with Time Windows Path Planning</article-title><source> Journal of Industrial Engineering</source><volume> 15</volume>,<fpage> 94</fpage>-<lpage>99</lpage>.<pub-id pub-id-type="doi"></pub-id></mixed-citation></ref><ref id="scirp.44187-ref15"><label>15</label><mixed-citation publication-type="journal" xlink:type="simple"><name name-style="western"><surname>Xu</surname><given-names> L.R. </given-names></name>,<etal>et al</etal>. (<year>2013</year>)<article-title>Based on LINGO of City Logistics Distribution Path Optimization</article-title><source> Journal of Electronic Design Engineering</source><volume> 276</volume>,<fpage> 52</fpage>-<lpage>54</lpage>.<pub-id pub-id-type="doi"></pub-id></mixed-citation></ref></ref-list></back></article>