物流管理英文文献以及翻译

An internet—based logistics management system for enterprise

chains

N. Prindezis，C。T. Kiranoudis

School of Chemical Engineering，NationalTechnicalUniversity，15780 Athens，

Greece

Received 13 September 2003；received in revised form 20 December 2003; accepted

27 January 2004

Available online 10 December 2004

Abstract

This paper presents an Internet-Based Logistics Management System to coordinate and disseminate tasks and related information for solving the heterogeneous vehicle routing problem using appropriate metaheuristic techniques，for use in enterprise chainnetworks。Its architecture involves a JA V A Web applet equipped with interactive communication capabilities between peripheralsoftware tools. The system was developed in distributed software fashion technology for all computer platforms utilizing a Webbrowser，focusing on the detailed road network of Athens and the needs of the Athens Central Food Market enterprises. 2004 Elsevier Ltd。All rights reserved.

Keywords: Decision support system；e-Logistics；Transportation; Vehicle routing problem

1.Introduction

Enterprise chains are the business model of the present and future regarding markets that involve small andmedium company sizes. Clearly, grouping activities towards a focused target facilitates an understandably improved market penetration guaranteed by a successfultrademarkofaleadingcompanyinthefield.Several collaboration models that basically include franchising areintroduced as a part of this integrated process. Whensuch a network is introduced in order to exploit acommercial idea or business initiative and subsequentlyexpanded as market penetration grows，several management issues arise regarding the operations of the entirenetwork。Such a network is the ideal place for organizing and evaluating in a more centralized way several ordinary operations regarding supply chain and logisticsInfact，toolsdeveloped fororganizingmanagementprocesses and operational needs of each individual company, can be developed in a more centralized fashionand the services provided by the tool can be offered toeach network member to facilitate transactions andtackle

operations similarly。Web—based applicationsare an ideal starting place for developing suchapplications.Typically such systems serve as a central depot fordistributing common services in the field of logistics.The commercial application is stored in a central serverand services are provided for each member of the group.A prototype of such a server is described in a previouswork (Prindezis, Kiranoudis，& Marinos-Kouris,2003).Thispaperpresentsthecompletedinternetsystemthat is installed in the central web server of the AthensCentral Food Market that deals with the integratedproblemofdistributionfor690companiesthatcomprisea unique logistics and retail chain of enterprises。Theneeds of each company are underlined and the algorithms developed are described within the unified internet environment. The problem solved and servicesprovidedforeachcompanyistheoneinvolvingdistribution of goods through a heterogeneous fleet of trucks.New insights of the metaheuristics employed are provided。A characteristic case study is presented to illustrate the effectiveness of the proposed approach for a real-world problem of distribution through the detailedroad network of Athens。

2. Distribution through heterogeneous vehicle fleets

The fleet management problem presented in this paper requires the use of a heterogeneous fleet of vehiclesthat distribute goods through a network of clients (Tarantilis，Kiranoudis，& Vassiliadis，2003，2004）。Therefore, the system was designed in order to automatically generate vehicle routes (which vehicles should de—

liver to which customers and in which order)，usingrational, quantitative，spatial and non-spatial information and minimizing simultaneously the vehicle costand the total distance travelled by the vehicles, subjectto the following constraints：

●each vehicle has a predetermined load capacity，typically different from all other

vehicles comprising thefleet (heterogeneous nature),

●the capacity of a vehicle cannot be exceeded，

● a single vehicle supplies each customers demand,

●the number of vehicles used is predetermined。

The problem has an obvious commercial value and hasdrawntheattentionofORcommunity.Itsgreatsuccess can be attributed tothe fact that it isa very interesting problem both from the practical and theoreticalpoints of view. Regarding the practical point of view,the distribution problem involved definitely plays a centralroleintheefficiencyoftheoperationalplanninglevelof distribution management，producing economicalroutes that contribute to the reduction of distributioncosts, offering simultaneously significant savings in allrelated expenses （capital, fuel costs，driver salaries）。ItsImportanceinthepracticallevel，motivatedintensetheoretical work and the development of efficientalgorithms. FortheproblembyacademicresearchersandprofessionalsocietiesinOR/MS，resultinginanumberofpapersconcerningthedevelopmentofanumberofVehicleRoutingInf

ormation Systems (VRIS）for solving the problem。The problem discussed is an NP—hard optimizationproblem, that is to say the global optimum of the problem can only be revealed through an algorithm of exponentialtimeorspacecomplexity withrespecttoproblemsize。Problems of this type are dealt with heuristic ormetaheuristic techniques。Research on the developmentof heuristic algorithms （Tarantilis ＆Kiranoudis，2001,2002a, 2002b）for the fleet management problem hasmade considerable progress since the first algorithmsthat were proposed in the early 60s。Among them, tabusearch is the champion (Laporte, Gendreau，Potvin，&Semet，2000）. The most powerful tabu search algorithmsare now capable of solving medium size and even largesize instances within extremely small computationalenvironments regarding load and time. On the algorithmic side，time has probably come to concentrate on thedevelopment of faster，simpler (with few parameters）and more robust algorithms, even if this causes a smallloss in quality solution. These attributes are essential ifan algorithm is to be implemented in a commercialpackage.

The algorithm beyond the system developed is oftabu search nature。As mentioned before, since the algorithms cannot reveal the guaranteed global optimum，the time that an algorithm is left to propose a solutionto the problem is of utmost importance to the problem.Certainly, there is a trade-off between time expected forthe induction of the solution and its quality。This partwas implementedinastraightforwardway.Ifthesystemis asked by the user to produce a solution of very highquality instantly，then an aggressive strategy is to beimplemented。If the user relaxes the time of solution tobe obtained, that is to say if the algorithm is left tosearch the solution space more effciently，then there isroom for more elaborate algorithms.

The algorithm employed has two distinct parts. Thefirst one is a generalized route construction algorithmthat creates routes of very good quality to be improvedby the subsequent tabu phase。The construction algorithm takes into account the peculiarities of the heterogeneous nature of fleet and the desire of the user to usevehicles of his own desire, owned or hired, according tohis daily needs。

The Generalized Route Construction Algorithm employed，is a two—phase algorithm where unrouted customers are inserted into already constructed partialsolutions. The set of partial solutions is initially empty,and in this case a seed route is inserted that containsonly the depot。Rival nodes to be inserted are thenexamined。

All routes employed involve single unrouted customers. The insertion procedure utilizes two criteria c1(i,u，j）and c2（i,u,j）to insert a new customer u between twoadjacent customers i and j of a current partial route.The first criterion finds the best feasible insertion point （i *,j *) that minimizes the Clark and Wright saving calculation for inserting a node within this specific insertionpoint,

C1（i,u，j)=d(I,u)+d(u，j)—d(I，j）（1）

In this formula，the expression d(k,l) stands for theactual cost involved in covering the distance betweennodes k and l。The Clark and Wright saving calculationintroduced in this phase serves as an appropriate strongintensification

technique for producing initial constructions of extremely good quality, a component of utmost

necessity in tabu improvement procedure. Thesecondphaseinvolvestheidentificationoftheactual best node to be inserted between the adjacent nodepair (i＊,j *）found in the first phase (Solomon, 1987）.From all rival nodes，the one selected is the one thatmaximizes the expression

C2 （i*, u，j *)=[d(0,u)+d(u,0）]—C1（i＊, u, j *）（2)

where 0 denotes the depot node. The expression selectedis the travelling distance directly from/to the depot to/from the customer and the additional distance expressed by the first criterion. In all，the first phase of the construction algorithm seeks for the best insertion point inall possible route seeds and when this is detected，theappropriatenodeisinserted。Ifnofeasiblenodeisfound,a new seed route，containing a single depot，is inserted。Thealgorithmiteratesuntiltherearenounroutednodes。Itmustbestretchedthatthewayroutesarefilledupwithcustomers is guided by the desire of the user regarding

theutilizationofhisfleetvehicles。Thatistosay,vehiclesare sorted according to the distribution and utilizationneeds of the dispatcher. Vehicles to be used first (regarding to user cost aspects and vehicle availability) will beloaded before others that are of lower importance tothe user. Typically，all users interviewed expressed thedesire for the utilization of greater tonnage vehicles instead of lower tonnage，so vehicles for loading weresorted in descending order of capacity.

For the subsequent aggressive part of the algorithm atabu search metaheuristic was implemented。The basiccomponents of this algorithm employed in this application are the neighbourhood definition, the short-termmemory and the aspiration criterion.

2.1。Neighbourhood

The neighbourhood is defined as a blend of the mostfavorable local search moves that transforms one solution to another. In particular, in its tabu search iterationthe type of move adopted is decided stochastically。Apredefined probability level is assigned to each movetype。After that，it is decided whether the move operation is performed within a single route or between different routes，once more stochastically. This time，for bothoperations, the probability level is assigned a value of50％. Subsequently，the best neighbour that the selectedmove implies is computed。The move types employedare the 2-Opt move （Bell et al。, 1983），the 1–1 Exchangemove (Evans&Norback, 1985），the1–0 Exchangemove(Evans ＆Norback, 1985), on both single route and different routes。

2。2. Short-term memory

Short-term memory，known as tabu list，is the mostoften used component of tabu search. Tabu list is imposed to restrict the search from revisiting solutions thatwere considered previously and to discourage the searchprocess from cycling between subsets of solutions. Forachieving this goal，attributes of moves, more preciselythe reversals of the original ones, are stored in a tabulist. The reversal moves that contain

attributes storedin tabu list are designated tabu and they are excludedfrom the search process。Regarding the tabu search variant implemented, these attributes are the nodes involved in the move （all the moves used in the thismethod can be characterized by indicating only twonodes) and the corresponding routes where these nodesbelongto.The number ofiterationsthatarcs'mobilityisrestricted is known as tabu list size or tabu tenure. Themanagement of the tabu list is achieved by removing themove which has been on the tabu list longest.

2.3。Aspiration criterion

The aspiration criterion is a strategy for overridingthe short-term memory functions. The tabu searchmethod implemented，uses the standard aspiration criterion：if a move gives a higher quality solution than thebest found so far, then the move is selected regardlessits tabu status。

Tabu Search algorithm terminates when the numberof iterations conducted is larger than the maximumnumber of iterations allowed。

3。Developing the internet-based application tool

Web services offer new opportunities in businesslandscape, facilitating a global marketplace where business rapidly create innovative products and serve customers better. Whatever that business needs is,Web services have the flexibility to meet the demandand allow to accelerate outsourcing。In turn，the developer can focus on building core competencies to createcustomer and shareholder value. Application developmentisalsomoreefficientbecauseexistingWebservices,regardless of where they were developed，can easily bereused。

Many of the technology requirements for Web services exist today，such as open standards for businessto-business applications，mission-critical transactionplatforms and secure integration and messaging products。However, to enable robust and dynamic integration of applications, the industry standards and toolsthat extend the capabilities of todays business—to—business interoperability are required。The key to taking fulladvantage of Web services is to understand what Webservices are and how the market is likely to evolve。One needs to be able to invest in platforms and applications today that will enable the developer to quickly and effectively realize these benefits as well as to be able tomeet the specific needs and increase businessproductivity。

Typically,therearetwobasictechnologiestobeimplemented when dealing with internet—based applications;namely server-based and client-based。Both technologies

have their strong points regarding development of thecode and the facilities they provide。Server—based applications involve the development of dynamically createdweb pages. These pages are transmitted to the webbrowser of the client and contain code in the form ofHTML and JA V ASCRIPT language。The HTML partis the static part of the page that contains forms andcontrols for user needs and the JA V ASCRIPT part isthe dynamic part of the page。Typically，the structureof the

code can be completely changed through theintervention of web server mechanisms added on the

transmission part and implemented by server-based languages such as ASP, JSP, PHP, etc. This comes to thedevelopment of an integrated dynamic page applicationwhere user desire regarding problem peculiarities （calculating shortest paths, execute routing algorithms, transact with the database，etc.）is implemented byappropriately invoking different parts of the dynamiccontent of such pages。In server—based applications all

calculations are executed on the server. In client-basedapplications, JA V A applets prevail。Communication ofthe user is guaranteed by the well-known JA V A mechanism that acts asthe medium between theuser and code。

Everything is executed on the client side。Data in thiscase have to be retrieved，once and this might be thetime-consuming part of the transaction。

In server-based applications, server resources areused for all calculations and this requires powerful server facilities with respect to hardware and software. Client-based applications are burdened with datatransmission (chiefly related to road network data)。There is a remedy to that；namely caching。Once loaded，they are left in the cache archives of the web browser tobe instantly recalled when needed。

In our case，a client-based application was developed。The main reason was the demand from the users pointof view for personal data discretion regarding their clients。In fact，this information was kept secret in our system even from the server side involved.

Data management plays major role in the good function of our system。This role becomes more substantialwhen the distribution takes place within a large anddetailed road network like this of a major complexcity。More specifically，in order to produce the proposed the routing plan, the system uses informationabout：

●the locations of the depot and the customers withinthe road network of the city

(their co-ordinatesattached in the map of the city)，

●the demand of the customers serviced，

●the capacity of the vehicles used，

●the spatial characteristicsof road segmentsof the network examined，

●the topography of the road network，

●the speed of the vehicle，considering the spatial characteristics of the road and

the area within of which ismoved,

●the synthesis of the company fleet of vehicles。

Consequently，the system combines, in real time，theavailable spatial characteristics with all other information mentioned above, and tools for modelling，spatial,non-spatial，and statistical analysis，image processingforming a scalable，extensible and interoperable application environment。

The validation and verification of addresses of customers ensure the accurate estimation of travel timesand distances travelled. In the case of boundary in thetotal route duration, underestimates of travel time maylead to failure of the programmed routing plan whereasoverestimates can lower the utilization of drivers and

vehicles，and create unproductive wait times as well （Assad, 1991). The data corresponding to the area of interest involved two different details. A more detailednetwork，appropriately for geocoding （approximately250,000 links) and a less detailed for routing (about10，000 links)。The two networks overlapped exactly。The tool that provides solutions to problems of effectively determining the shortest path，expressed in termsoftraveltimeordistancetravelled,withinaspecificroadnetwork,usingtheDijkstra’sal gorithm（Winston，1993)。In particular, the Dijkstra’s algorithm is used in twocases during the process of developing the routing plan。In the first case，it calculates the travel times between allpossible pairs of depot and customers so that the optimizerwould generate thevehicleroutesconnectingthemandinthesecondcaseitdeterminestheshortestpathbetwe en two involved nodes (depot or customer）in therouting plan, as this was determined by the algorithmpreviously. Due to the fact, that U-turn and left—,right—turn restrictions were taken into considerationfor network junctions, an arc-based variant of the algorithm was taken into consideration （Jiang，Han, &Chen, 2002）.

The system uses the optimization algorithms mentioned in the following part in order to automaticallygenerate the set of vehicle routes (which vehicles shoulddeliver to which customers and in which order）minimizing simultaneously the vehicle costs and the total distance travelled by the vehicles This process involvesactivities that tend to be more strategic and less structured than operational procedures. The system helps

planners and managers to view information in newway and examine issues such as:

●the average cost per vehicle，and route，

●the vehicle and capacity utilization,

●the service level and cost,

●the modification of the existing routing scenario byadding or subtracting

customers.

In order to support the above activities，the interfaceof the proposed system provides a variety of analyzedgeographic and tabulated data capabilities. Moreover,the system can graphically represent each vehicle routeseparately, cutting it o？from the final routing plan and offering the user the capability for perceiving the roadnetwork and the locations of depot and customers withall details.

4。Case study

The system developed was used in the Central FoodMarket of Athens, Greece. The specific Market involves2an area of 320，000m in the south—west region of Athensgreater area (Agios Ioannis Rentis，Athens, Greece）atthe boundary of port of Pireaus，Greece. This Marketis basically a hybrid of two submarkets; the first one involves fresh vegetables and fruits and the second onefresh meat。A Central Food Market is an organizationthat involves numerous small enterprises that sell

anddistribute fresh food products，chiefly fresh vegetables，fruits fish and meat. It is considered to be the placewhere supply and demand come together and whereprices are determined in conditions of transparencyand open exchange。Every day，the market is visitedby thousands of operators and traders who consider itthe best place in which to carry out their transactions。Themarketisusedbycompaniesspecializinginthefoodsector, traditional retailers, the city markets, supermarkets, hypermarkets，hotel and catering establishments.

The fresh vegetables and fruits market involves 690small and medium enterprises that cover an area of27，100m , while the Meat market involves 105 small2and medium enterprises that cover an area of 6050m 。As a complementary area to the Markets，Athens Central Food Market has a Services and Warehouses Area,to serve the growing economic activity generated by theFoodUnit。Cash&Carry,purchasecenters，distributionand logistics，storage, handling and packaging, coldstoresavailableforrent，motor vehicleservices.Inshort，all the services operators required。The market need for effcient logistics requires specialization and investment

（trucks, cold stores，etc。), in order to be competitiveand provide the growing level of service demanded.Every day，this market complex offers a selection offruits and vegetables, both in the range of productsand varieties and in the sheer volume on offer, whichmakes it the largest fruit and vegetable market in GreeceandoneofthelargestinEurope。AthensCentralMarketresponds to the challenge of effciently and reliably serving the most important food sector in Greece，offering awide variety of vegetables，fruits, meats，meat productsinunrivalledconditionsofhygiene andsafety。The MeatMarket is concerned not only with distribution but alsowith production. Many farmers participate directly inthe Athens Central Market，as it actively promotesproducts with denomination of origin and quality certificates. Athens Central Market installations involveroughly 500 parking places.

The application can be found at the internet addresshttp://www。okaa.gr/router/default。asp, through securecookie entrance。The system was appropriatelycoded in the form of a java applet encapsulated in aWeb page accessible by the users through the Web Server of the organization。There were several restrictionsthat were taken into consideration as user requirements。The application had to be compact, user-friendly，thedata entered that would concern a specific enterprisecould not be transparent to others，including the organization and full reports ready to use by truck drivers hadto be generated.

5. Conclusions Thispaperpresentedansystemtocoordinateanddisseminate tasks and related spatial and non-spatial information for solving the heterogeneous vehicle routingproblem using metaheuristic algorithms。This systemusedtoautomaticallygeneratevehicleroutingplanssuchthatallcustomersdemands

weremet,noconstraintswereviolated and a combination of vehicle costs and distancetravelled was minimized. The architecture of the systemwas based onan integrated JA V A WebAppletequippedwith interactive communication capabilities betweenperipheralsoftwaretools.Thesystemthatwasdevelopedin distributed software fashion technology for all Webbrowsersrunningonanyplatform,anditwassuccessfullyapplied to the area of Greater Athens for the benefits ofAthens Central Food Market enterprises。

基于互联网的连锁企业的物流管理系统

N. Prindezis,C.T. Kiranoudis

化工学院，国立技术大学,15780雅典，希腊

收到2003年9月13日，在经修订的形式收到的2003年12月20号,接受2004

年1月27日

可在线二〇〇四年十二月十日

摘要

本文介绍了一种基于Internet的物流管理系统，以协调和传播解决异构车辆路径问题采用适当的启发式技术，任务和相关信息，为企业的连锁网络作品的使用。其体系结构包括一个JA V A的Web小程序与外设之间的互动沟通的软件工具的功能配备。该系统的开发方式,在分布式软件技术的所有电脑使用一个WebBrowser平台，在雅典的详细道路网络为重点和雅典中央食品市场企业的需要。2004 Elsevier公司保留所有权利.

关键词：决策支持系统，电子物流，运输，车辆路径问题

1、前言

企业连锁经营模式是对当前及未来的市场，包括中小型公司规模。显然，使集团的重点目标是可以理解的活动有利于提高市场占有率由一家公司成功的商标保证在外地。几个合作模式，基本上包括引入特许经营作为这一进程的一部分。当这种网络的引入，以利用商业理念或企业的倡议，并随后扩大市场渗透率的增长，若干管理问题方面出现的整个网络的运作.这种网络是组织和较集中的方式对一些普通业务供应链和物流从评估的理想场所,工具，组织管理流程及个别公司的业务需要开发的，可以更集中的方式发展和该工具提供的服务可以提供给每个网络成员促进交易和处理业务类似.基于Web的应用是一个理想的起点为开发此类应用的地方。通常这些系统作为分配在物流领域的共同服务的中心仓库。商业应用存储在中央服务器和服务的每个组的成员提供。一个这样的服务器原型描述了以前的工作（Prindezis，Kiranoudis，库里斯,2003年）。

本文介绍了完成跨网系统,在雅典中央副食品批发市场中央Web服务器上安装的处理分配690公司，包括一个独特的物流和零售连锁企业的整合问题.每家公司的需要是强调和算法开发的范围内统一的网络环境描述。解决问题和服务的每一个公司提供的是一个涉及通过混合车队的卡车货物分配。严谨启发式解法为就业提供新的见解.阿特征的案例研究，提出说明，通过详细的道路网络雅典的一个现实世界的分布问题提出方法的有效性。

2、通过异构车队分布

该舰队管理问题本文提出需要的车辆混合车队使用的方式来分配网络的客户货物

（Tarantilis,Kiranoudis，及阿迪斯,2003，2004）.因此，该系统是为了设计，自动生成车辆路线（即车辆应提供哪些客户的顺序),使用合理，数量,空间和非空间信息和车辆，同时尽量减少成本和总距离行驶的车辆，须符合下列限制：

●每辆车有一个预先确定的负载能力,通常是由组成的船队（异质性）的所有其

他车辆不同，

●车辆的能力，不能超越，

●一个单一的汽车用品每个客户的需求，

所用车辆的数目，预先确定的。

这个问题具有明显的商业价值，已引起或社会的关注.它的巨大成功可以归功于以下事实:这是一个无论从实用的角度来看,和理论很有趣的问题.关于实际角度来看，问题所涉及的分布起着一定的分配管理的业务水平，提高效率的中央计划的作用，产生经济的路线，有助于降低分销成本，同时提供显着的一切有关费用节省（资本，燃料费用，司机工资)。它的重要性，在实践上，在紧张的理论工作动机和高效率的算法。

对于学术研究机构及专业团体在OR / MS分析问题，在一个关于解决问题的车辆路由信息系统(VRIS）数量发展论文的数目。讨论的问题是一个NP难优化问题，即在全球的优化问题只能通过对指数的时间和空间复杂度算法透露有关问题的大小。存在的问题与启发式或启发式技术对付这种类型。对启发式算法的开发研究（Tarantilis＆Kiranoudis,2001，2002～2002年）为车队管理问题，取得了自认为是在60年代初首次提出的算法相当大的进展。其中，禁忌搜索是冠军（拉波特，根德罗，普托文，及Semet，2000）.最强大的搜索演算法现在是解决中等规模，甚至大型工程在时间方面的负荷,极少数情况下，能够计算环境。在算法方面，时间大概要集中精力，快，简单(与发展的几个参数)和更强大的算法,即使这导致在品质的解决方案小的损失。这些属性是必不可少的，如果一个算法是在一个商业软件包实施.

发达国家以外的系统算法是搜索的性质。如前所述，由于算法可以保证没有透露全局最优的一个算法是留给提出解决问题的时间是非常重要的问题.当然,有一个与贸易之间的休息时间的解决方案，并诱导其质量的预期。这部分是执行一个简单的方法。如果系统询问用户生产出高品质的解决方案,即刻，那么积极的战略的实施程序。如果用户放松时间的解决方案要获得,也就是说,如果该算法留下来搜索解空间更高效，那么就有更加详细的算法空间。

该算法采用了两个不同的部分。第一个是广义的路线构造算法创建质量很好的路线，被后面的阶段改善.建造算法考虑到了车队的不同性质和特点的用户希望利用自己的意愿拥有或租用的车辆，根据他的日常需要。

广义算法就是，是一个两阶段算法在未布线客户到已建成的部分解决方案插入。部分解决方案的设置最初是空的,在这种情况下，插入种子路线只包含仓

库。竞争对手节点插入，然后检查所有路线就业涉及单未布线的客户。插入过程采用两个标准的C1（i，u，j）和C2（i,u,j）之间插入两个相邻的客户提供了新的客户用户接口和当前部分路线ĵ。第一个标准，找到最佳可行插入点（i ＊,j＊）最小化的在这个特定的插入点插入一个节点的计算，

C1（i,u，j）=d(I，u)+d（u，j）-d(I，j) (1）

在这个公式中，D表达式（k,1）代表在覆盖节点之间的距离,k和湖所涉及的实际成本克拉克和赖特的节能计算在这个阶段推出可作为适当的生产结构的初步非常好的质量，在改善过程中是极为必要组成强有力的加强技术.

第二阶段是实际确定最佳节点之间必须相邻节点插入（i＊，j ＊)在第一阶段（所罗门,1987年）发现.从所有竞争对手节点,选择一个最大化的表达C2 (i＊, u, j *）=[d（0,u)+d(u,0)］—C1(i＊, u, j ＊) (2）其中0表示车厂节点.表达式选择行驶距离是直接从/到站到/从客户和额外的距离表示。

由第一个标准，总之，建筑算法的第一阶段要求在所有可能的途径种子最佳的插入点，当这是检测到相应的节点插入.如果没有找到可行的节点，一个新的种子路线，其中包含一个仓库，插入。

该算法迭代，直到没有未布线节点。必须延伸路线的方式与客户充满了由有关用户的愿望指导。

车队车辆的利用率。这就是说，车辆进行排序按照分配和调度运用的需要。车辆首先要使用(关于用户的成本和车辆方面的情况）将提交给别人，而较低的重要性，用户加载。通常情况下，所有用户访问表示有更大吨位的车辆，而不是利用低吨位的愿望，因此,装载车辆降序秩序的能力.

对于随后的搜索算法的启发式实施积极的一部分。在此应用程序采用这种算法的基本组成部分是附近的定义，短期记忆和期望的标准。

2.1邻里

附近的定义是最有利的本地搜索动作，变换另一种解决办法融合。特别是,通过在其禁忌搜索迭代的移动类型随机决定。预定义的概率水平,分配给每个移动类型。在此之后，决定是否执行移动操作是在一个单一的路线或不同的路线，再次随机.这一次,这两个行动的概率水平分配50％的价值.随后，最好的邻居

说，此举意味着选择计算。此举类型就业是2选项移动(贝尔等人。，1983），交易所将在1-1（埃文斯与努尔贝克，1985)，当前第1页— 0 移动交换（埃文斯与努尔贝克，1985年），单路和不同路线。

2。2短期记忆

短期记忆,因为禁忌名单称为，是禁忌搜索最常用的组成部分。禁忌名单去限制从重新被认为以前并劝阻，从解决方案的子集之间的循环搜索过程的解决办法。为实现这一目标,属性的动作，更准确地原有的的逆转，被存储在一个禁忌名单。逆转动作，包含属性禁忌列表存储在指定禁忌，他们在搜索过程之外。关于禁忌搜索变种实施，这些属性是在移动过程中的节点（所有的动作中使用的这种方法可以通过指出只有两个节点的特点）和在这些节点属于相应的路线。这个数字是；灵活限制被称为禁忌列表的大小或禁忌的任期。禁忌的列表管理是通过消除已禁忌名单上最长的已移动。

2。3标准意愿

标准的愿望是压倒一切的短期记忆功能的策略。禁忌搜索方法的实施，使用标准的期望标准：如果此举给出了更高质量的最佳解决方案，比迄今为止发现的话，将被选中，不论其禁忌的地位.禁忌搜索算法终止时的迭代次数进行比允许的最大数量较大的迭代。

3、发展基于互联网的应用工具

Web服务提供的商业景观的新机会,促进全球市场在业务快速推出创新的产品和客户提供更好的服务.无论是企业需要的是,Web服务可以灵活地满足需求，并允许加速外包。反过来，开发人员可以专注于构建核心竞争力，创造客户和股东价值。应用程序开发，也更有效，因为现有的Web服务,无论他们在那里开发的，可以很容易地重用。

对网络服务的技术要求，很多今天存在的，如营业标准，业务应用，关键任务交易平台和安全的一体化和信息产品.不过,为使强大和动态系统的综合应用，行业标准和工具，扩大天的业务能力，对企业的互操作性是必需的。在采

取了充分利用网络服务的关键是要了解什么是Web服务，以及如何在市场可能发生变化。人们需要能够在今天的平台和应用的投资,使开发人员快速而有效地实现这些好处，也能够满足特定需求，提高企业的生产力.

通常，有两种实施处理时,互联网的应用程序，即基于服务器和基本技术，基于客户的。这两种技术

有自己的长处对代码的发展和它们所提供的设施。服务器的应用程序涉及的动态创建的网页的发展.这些网页传送给客户端的网络浏览器和包含在HTML和JavaScript语言形式的代码。部分的HTML的网页，其中包含形式和用户需求和JavaScript的部分控制部分是静态页面的动态部分.通常情况下，代码的结构完全可以通过干预机制的Web服务器上的改变增加

传动部分和服务器实现基于如ASP，JSP，PHP和语言等，这涉及到一个综合的动态网页应用程序开发的用户希望有关问题的特殊性（计算最短路径,执行路由算法，处理与数据库，等）是通过适当援引这些网页的动态内容的不同部分。在基于服务器的所有应用

计算在服务器上执行。在客户端的应用程序，Java小程序为准。用户的通信保障由著名的JA V A的机制,充当用户的代码。

一切都执行在客户端。在这种情况下的数据必须被检索，一次，这可能是费时的交易的一部分。在服务器的应用程序，服务器资源是所有计算中，这就要求有关的硬件和软件功能强大的服务器设施。基于客户端的应用程序与数据传输负担(主要是与道路网络数据）.有一个该补救方法，即缓存.一旦加载，他们留在Web浏览器的快取档案将在需要时立即召回。

就我们而言，客户端的应用程序的开发。主要的原因是从有关个人资料的客户自行查看用户的用电量。事实上，这些信息是保密的，甚至在我们的系统从服务器涉及的方面。数据管理在我们的制度好职能的主要作用。这种作用变得更为实质性的分配时，需要在一个像一个大的城市大型复杂和详细的道路网进行.更具体地说，为了生产计划提出的路线,系统使用的信息：

●在城市道路网在车厂地点和客户（他们统筹重视在城市地图）接受服务

的客户的需求，

●所用车辆的能力，

●的净工作道路部分的空间特征研究，

●道路网地形，

●车辆的速度，考虑到道路的空间特征和地区范围内的移动，

●该公司车队车辆的合成。

因此,该系统结合实时,可用空间特征与上述其他所有信息，以及造型,空间，非空间，和统计分析工具，图像处理形成一个可伸缩，可扩展和可互操作的应用环境。验证和核查，确保客户的地址的旅行时间和旅行距离准确估计。在边界线的总时间的情况，可能导致低估了，而高估了编程路由计划可以降低司机的利用和失败的旅行时间车辆，并建立非生产性等待时间，以及（阿萨德，1991）。数据对应感兴趣的区域,涉及两个不同的细节。更详细的网络,适当地地理编码（约250，000链接）和更少的路由（约10，000个链接）详细。两个网络完全重叠。该工具提供了解决方案有效地确定最短路径问题，在旅行时间和旅行距离来计算，在一个特定的道路网络，利用Dijkstra算法（温斯顿，1993年）。特别是，Dijkstra算法是在两种情况下使用，在发展过程中的路由计划.在第一种情况，它计算之间的车厂和可能对所有客户的旅行时间，以便优化器将生成的车辆路线连接并在第二种情况下它决定了涉及两个节点（仓库或客户中）最短路径路由计划，因为这是确定先前的算法.由于这样的事实，即掉头和左,右转向限制是考虑到网络的路口,一个弧形的算法的变种考虑（江，韩，及陈，2002）。

该系统使用的算法在以下部分中提到的优化，以自动生成车辆路线设置（即车辆应提供哪些客户的顺序)，同时最大限度地减少车辆的费用和总距离行驶的车辆,这一过程涉及活动往往更具有战略性和业务程序不到结构.该系统可以帮助规划人员和管理人员，以查看新的方式的信息和研究的问题,例如：

●每辆车的平均成本，和路线，

●车辆和产能利用率，

●服务水平和成本，

●通过增加或减少客户现有的路由方案的修改。

为了支持上述活动，拟议的系统接口提供了各种分析和列的地理数据功能.此外，该系统可以图形方式表示每辆汽车的路线分别削减它从最后的路由计划和为用户提供了感知的道路网络,并与所有细节车厂和客户的地点的能力。

4、案例研究

该系统研制的用于中央食品市场的希腊雅典。具体的市场涉及2 32万平方米的西南地区大面积在雅典的比雷埃夫斯,希腊港口边界（Ioannis伦蒂斯，雅典，希腊)地区.这个市场基本上是两亚市场杂交种；的第一项是新鲜蔬菜和水果,第二个鲜肉。阿中央粮食市场是一个组织,涉及众多的小企业，销售和分发新鲜食品,主要是新鲜蔬菜，水果，鱼和肉.它被认为是地方供求走到一起，在价格中的透明度和公开交换条件决定的。每天,市场是由访问的运营商和贸易商谁认为这是最好的地方，进行他们的交易数以千计。市场是利用在粮食部门的专业公司,传统的零售商，在城市市场，超市，大卖场，酒店和食肆。新鲜的蔬菜和水果市场,涉及690中小型企业，涵盖了21700平方米面积，而肉类市场涉及105个小型和中小型企业，涵盖了6050平方米领域。作为补充的市场领域，雅典环副食品批发市场的服务业和仓库区，为日益增长的经济活动所产生的食品股。现购自运，采购中心，分销和物流，仓储,装卸和包装,可租用冷库，汽车服务、所有的服务运营商需求。对于高效率的物流市场的需求，需要专业化和投资（车，冷藏库等)，以具有竞争力和提供的服务水平要求越来越多。每一天，这个市场提供了一个复杂的水果和蔬菜的选择，在产品的品种和发行量巨增，这使得它的各种中,最大的水果和蔬菜市场，在希腊和欧洲最大的之一.雅典中央市场响应了高效挑战和可靠地服务于希腊最重要的粮食部门,提供蔬菜，水果,肉类,在卫生和安全条件的肉类产品无与伦比的多种。在肉类市场关注的是,不仅分布，而且与生产.许多农民直接参与雅典中央市场，因为它积极推动与原产地和产品质量认证证书面额。雅典中央市场设施包括约500个停车位。

应用程序可在互联网地址http：//www。okaa.gr/router/default。asp，通过安全Cookie的入口。该系统在适当的编码在一个封装的网页，通过该组织的Web 服务器的用户访问了Java applet的形式。有报道说，考虑到了用户需求数的限制.应用程序必须紧凑，方便用户，输入的数据，将特定的企业的关注不能是透

明的其他方面，包括组织和备用卡车司机等。

5、结论

提出一种制度,以协调和传播任务和有关空间和非解决异构车辆路径问题使用启发式算法的空间信息。用于自动生成车辆调度计划等，所有客户的要求得到满足，没有任何限制，受到侵犯和车辆费用组合和路程的距离减少到最低限度这一制度。该系统的架构是基于JA V A的网络集成外设之间的互动沟通的软件工具性能都有小程序。即在分布式软件技术开发的方式为所有网站在任何平台上运行的浏览器系统,它成功地应用于雅典中部的食品市场企业的利益在雅典地区.