用多個(gè)配送中心來(lái)建立城市配送模型解決配送問(wèn)題外文翻譯

1、用多個(gè)配送中心來(lái)建立城市配送模型解決配送問(wèn)題外文翻譯 外文翻譯原文Modelization of Time-Dependent Urban Freight Problems by Using a Multiple Number of Distribution Centers Material Source: Netw Spat EconAuthor: David Escuín?Carlos As time goes on and because of population increase in large cities, the problems generated by urba

2、n freight distribution are getting more and more complicated due to traffic flow, traffic congestion, illegal parking, just-in-time delivery, time constraints, e-commerce and, above all, pollution and environmental impact. Although the literature on solving routing and scheduling problems is very ex

3、tensive nowadays, almost no models exist that take hubs into account, and so, from the point of view of research, it is still necessary to find ways of resolving the negative effects caused by the above-mentioned points, through an analysis of new delivery strategies and algorithms. The aim of the p

4、aper is to model urban distribution vehicle routing problems by means of hubs in large cities. Hubs are very well known in the literature; they are often used in many scheduling problems and strategy models, like air traffic models, logistic models, etc. Over the last few years, new distribution cen

5、ters called Urban Distribution Centers, U D Cs or D Cs have appeared within the cities. Finnegan et al. 2005, present a study evaluating sustainable freight distribution in the city center of Dublin, focusing particularly on urban distribution centers and managing the last mile delivery. The idea be

6、hind the urban distribution center is to provide buffer points where cargo and packages which are to be delivered to shops and businesses, can be stored beforehand. At these centers, there will be other kinds of routing problems corresponding to a fairly similar distribution problem One of the main

7、objectives of these centers is related to reducing traffic congestion caused by the large number of delivery trucks on the streets and because it is not possible to create enough parking places, in zones where problems such as illegal parking lead to reductions in traffic flow. As shops and business

8、es demand shorter and shorter delivery times, vehicle routing and scheduling problems become harder for distributors. It is recognized that the traditional system based on fixed routes does not fulfils the expectations of trade and may, in some cases, be quite inefficient for distributors. In this w

9、ork, a new vehicle routing model based on the known Time-Dependent Vehicle Routing Problem with Time Windows, TDVRPTW, Huey-Kuo et al. 2006 has been developed and a change in the traditional approach is proposed, by adopting a system in which some customers are served by urban distribution centers t

10、o be more specific, by using, for example, hybrid vehicles while the remaining customers are served by traditional routes. This study is also motivated by recent developments in real time traffic data acquisition systems, as well as national and international policies aimed at reducing concentration

11、s of greenhouse gases in the atmosphere emitted by traditional vans. Due to the fact that the density of shops differs greatly in central districts of a city compared to the outskirts, not all shops are serviced by routes starting at the hub. For this reason, it is suggested that the DCs be located

12、in areas where there is a high density of shops and that in other areas, deliveries be made directly through conventional distribution methods Fig. 1. The method used consists of extending the traditional VRPTW by giving further consideration to total delivery costs and the influence of arrival time

13、s at each DC. The paper is organized as follows: after this introductory section; a review of time dependent models is presented in the next section; then the model formulation is introduced in two parts?a problem description and a mathematical model. After introducing the model, which is the focus

14、of this paper, the solution algorithm is presented once the concept of latest possible departure time is explained in detail. The general scheme of the solution procedure is shown as well. At the end of this paper, in section 5, a case study involving a pharmaceutical distribution is presented to sh

15、ow the method and computational results. Finally, several findings and future work are discussed. Before proceeding to the description of the new model, some brief general concepts of Time Dependent Vehicle Routing Problems TDVRP are introduced. It is not necessary to explain the VRP models because

16、they have been largely studied The Time Dependent Vehicle Routing Problem TDVRP, another variant of the classic Vehicle Routing Problem, consists of optimally routing a fleet of vehicles of fixed capacity when travel times are time dependent, in the sense that the time employed to travel each given

17、arc depends on the time of day that the travel starts from its originating node. It is motivated by the fact that in urban contexts, variable traffic conditions play an essential role and cannot be ignored if a realistic optimization is to be achieved. An optimization method consists in scheduling,

18、planning and finding solutions that minimize three hierarchical objectives: number of routes, total travel time and cost. Mitrovi?-Mini? et al. 2004 proposes the use of a rolling time horizon for the standard solution methodology for the dynamic PDPTW. When assigning a new request to a vehicle, it m

19、ay be preferable to consider the impact of a decision on both a short and a long-term horizon. This way, in particular, better managing of slack time in the distant future may help reduce routing costs. On the other hand, Hashimoto et al. 2007, uses a local search to determine the routes of the vehi

20、cles. When evaluating a neighborhoods solution, they compute an optimal time schedule for each route. This sub-problem can be efficiently solved by dynamic programming, which is incorporated into the local search algorithm. The neighborhood of the local search contains slight modifications of the st

21、andard neighborhoods called 2-opt, Cross Exchange and Or-opt. The final aim is an algorithm that evaluates solutions in these neighborhoods more efficiently than those that compute the dynamic programming from scratch, as these utilize information from past dynamic programming recursions in order to

22、 evaluate the current solution. Another recent work can be found in Donati et al. 2008 wherein the time space in a suitable number of subspaces is discredited with a multi-ant colony system. Regarding urban environment, Friesz et al. 2008 discusses a model of dynamic pricing of freight services that

23、 follows the paradigm set in the field of revenue management for nonlinear pricing in a dynamic, game theoretic setting. They propose three main entities: sellers, transporters and receivers. Each competing agents extremely problem is formulated as an optimal control problem and the set of these cou

24、pled optimal control problems is transformed into a differential variation inequality representing the general Nash equilibrium problem. Ando and Taniguchi 2006 presents a model for minimizing the total costs incorporating the uncertainty of link travel times with the early arrival and delay penalty

25、 at customers who set up designated time windows. This paper presents calibration of the Vehicle Routing and scheduling Problems with Time Windows- Probabilistic. Casceta and Coppola 2003 review and classify models according to basic assumptions on the flow structure. Regarding locations of DCs, Sil

26、va and Serra 2007 propose a met heuristic to solve a new version of the imum Capture Problem. The Cap problem seeks the location of a fixed number of stores belonging to a firm in a spatial market where there are other stores belonging to other firms already competing for clients. Yam is et al. 2003

27、 present a simple simulation of road growing dynamics that can generate global features as belt-ways and star patterns observed in urban transportation infrastructure. Hsu et al. 2007 carries out a study focused on determining the optimal delivery routing, loads and departure times of vehicles, as w

28、ell as the number of vehicles required for delivering perishable food to many customers from a DC. Features related to delivery of perishable food were considered, such as the time-window constraints of customers and the stochastic characteristics of travel time and food preservation. Time-dependent

29、 temperatures, travel time and soft time-windows with penalty costs were further discussed, and modifications were accordingly made to both the objective functions and the constraints in the mathematical programming models. Regarding scheduling, one important aspect of this type of problem Mitrovi?-

30、Mini? and Laporte 2004 lies in analyzing two simple waiting strategies, Drive-First DF?a vehicle leaves its current location immediately, and Wait-First WF?a vehicle waits at its current location for as long as is feasible. The other two strategies introduced are Dynamic Waiting DW?the vehicle drive

31、s as soon as is feasible while serving close locations; when all such locations are served, then the vehicle has to serve the next furthest location and Advanced Dynamic Waiting ADW?propagate the total waiting time available on the route along the entire route, which are combinations of the two simp

32、le strategies. Solving a problem modeled as a VRPTW deals with calculating a solution based on a set of routes and a scheduling of the same; therefore, one only has to solve a single problem. However, by using k DCs, the whole problem is now comprised of k+1 problem: one special VRPTW in each DC bes

33、ides the main problem in which some customers and k DCs are serviced Each special VRPTW involves a subset of customers which are serviced by vehicles these may be hybrid vehicles starting from the DC. From now on, the routes and vehicles starting from the depot and the routes and vehicles starting f

34、rom the DCs, will be identified by first and second level routes and vehicles respectively. These two important remarks need to be discussed in more detail, as follows: a From the point of view of the dispatching center at the depot, each DC is considered in the light of another customer, with deman

35、ds of its own in addition to the demands of its associated customers. However, its time window is not a trivial issue as will be explained later. Therefore, apart from a reduction in the number of locations/customers, the original problem has yet another variant with respect to the original problem:

36、 the DC costs must be taken into account and added to the original costs. b Once the first level vehicles have serviced demand for one DC, the second level vehicle can already be loaded and, thereafter, can depart. At this point, note that the information data of the customers never changes and henc

37、e delivery is transparent for the customers associated with the DC; that is to say, these customers do not need to know whether the second level vehicles left from the depot or from the DC. 譯文用多個(gè)配送中心來(lái)建立城市配送模型解決配送問(wèn)題 資料來(lái)源: Netw Spat 經(jīng)濟(jì)周刊作者:大衛(wèi) 伊蘇卡隆 隨著時(shí)間的推移,由于城市人口的大量增加,由市區(qū)貨物配送所產(chǎn)生的問(wèn)題也越來(lái)越復(fù)雜,其原因可歸結(jié)于交通事故,交通

38、堵塞,非法泊車(chē),準(zhǔn)時(shí)交貨,時(shí)間的限制,電子商務(wù),其中最重要的是污染現(xiàn)象對(duì)于環(huán)境的影響。雖然如今關(guān)于解決線(xiàn)路和調(diào)度問(wèn)題的文獻(xiàn)是非常全面的,但是幾乎沒(méi)有任何成型的模式存在,考慮到其關(guān)鍵性,從研究的角度來(lái)看,它仍然需要尋找合適的方法來(lái)解決上述問(wèn)題所造成的負(fù)面影響,通過(guò)運(yùn)用一個(gè)新的策略和方法進(jìn)行分析。 本文的目的是在大城市中模擬城市配送車(chē)輛行駛線(xiàn)路。集線(xiàn)器是一本非常有名的文獻(xiàn),它往往應(yīng)用在許多調(diào)度問(wèn)題和戰(zhàn)略模式方面,如空氣流量模型,物流模型等,在過(guò)去的幾年里,新的配送中心(稱(chēng)為城市配送中心,U DCs或DCs)已經(jīng)出現(xiàn)在城市中。芬尼根等人(2005年),在都柏林市中心實(shí)施了一項(xiàng)有關(guān)可持續(xù)貨物配送的研究

39、,尤其關(guān)注城市配送中心和最后一公里交付的管理。 建立城市配送中心的目的是提供貨物和貨物包裝存放的緩沖區(qū),這是貨物在被傳遞到商店和企業(yè)前,可以進(jìn)行預(yù)先儲(chǔ)存的地方。在這些配送中心,將會(huì)出現(xiàn)類(lèi)似于相應(yīng)的路線(xiàn)分布的問(wèn)題。 這些配送中心的主要目標(biāo)之一是減少交通擁堵(都是由于街上的貨車(chē)過(guò)多,因?yàn)樗豢赡墚a(chǎn)生足夠的停車(chē)位),在配送區(qū)域內(nèi)的問(wèn)題,例如非法泊車(chē)導(dǎo)致交通流量減少。由于商店和企業(yè)要求的交貨時(shí)間越來(lái)越短,物流配送車(chē)輛的調(diào)度成為了分銷(xiāo)商迫切需要解決的問(wèn)題。人們認(rèn)識(shí)到,傳統(tǒng)體制下的固定配送路線(xiàn)已經(jīng)不能滿(mǎn)足貿(mào)易的期望,因?yàn)樵谀承┣闆r下,分銷(xiāo)商是非常低效的。 在這項(xiàng)工作中,新的車(chē)輛路線(xiàn)模型(基于已知的時(shí)間依賴(lài)

40、型車(chē)輛路線(xiàn)問(wèn)題的時(shí)間表,TDVRPTW,休伊闊等。2006年)已經(jīng)制定,并且在傳統(tǒng)方法上進(jìn)行了改變,提出采用統(tǒng)一的系統(tǒng),由城市配送中心為其中一些客戶(hù)提供服務(wù)(更豐富的的服務(wù)項(xiàng)目,例如,混合動(dòng)力汽車(chē)),而剩下的客戶(hù)是由傳統(tǒng)路線(xiàn)提供服務(wù)。這項(xiàng)研究是根據(jù)實(shí)時(shí)交通數(shù)據(jù)采集系統(tǒng)所開(kāi)展出來(lái)的,其目的和國(guó)家與國(guó)際政策的一樣,在于降低大氣中排放的溫室氣體濃度。 由于商店在城市中心區(qū)與郊區(qū)的分布密度差別是很大的,因此并不是所有的商店都能通過(guò)配送中心來(lái)提供服務(wù)。出于這個(gè)原因,配送中心應(yīng)該設(shè)在一個(gè)商店和人口高度集中的區(qū)域,通過(guò)傳統(tǒng)交付作出直接分配。 采用的方法應(yīng)該進(jìn)一步考慮延長(zhǎng)傳統(tǒng)VRPTW模型對(duì)于總交付成本和到達(dá)

41、時(shí)間在每個(gè)區(qū)域內(nèi)的影響。 本文結(jié)構(gòu)如下:在該段介紹后面,將會(huì)介紹一個(gè)時(shí)間依賴(lài)模型,然后將模型的制定分為兩部分,分別是數(shù)學(xué)模型的描述和介紹。在介紹了這個(gè)模型后將是本文的重點(diǎn)既解決算法,解釋了何為最快出發(fā)時(shí)間。該解決方案的過(guò)程總體顯示為良好。本文的最后部分,即案例研究,涉及到藥品徐徐求量的分布情況,以及相關(guān)的計(jì)算方法和計(jì)算結(jié)果。最后,討論了一些研究結(jié)果和未來(lái)所需要做的工作。 在描述新的模型之前,簡(jiǎn)要介紹一下時(shí)間依賴(lài)型車(chē)輛關(guān)于路徑問(wèn)題的(TDVRP)一般概念。這是一個(gè)沒(méi)有必要進(jìn)行解釋的VRP模型,因?yàn)樗呀?jīng)被廣泛應(yīng)用了。 時(shí)間依賴(lài)型的車(chē)輛路徑問(wèn)題(TDVRP),是另一種經(jīng)典的車(chē)輛路徑問(wèn)題的變型,包括

42、在固定時(shí)間內(nèi)制定最佳配送路線(xiàn)的問(wèn)題,車(chē)隊(duì)在一天時(shí)間內(nèi),從它的始發(fā)地出發(fā)。事實(shí)上,在城市環(huán)境中,可變交通條件發(fā)揮著重要的作用,如果要實(shí)現(xiàn)優(yōu)化,這是我們不能忽視的方面。一種合理的優(yōu)化方法包括安排,規(guī)劃和尋找解決辦法,其目的在于最大限度地減少三個(gè)層次目標(biāo):路線(xiàn),總行程時(shí)間和成本數(shù)。 米特羅維奇-銘尼科等(2004年)提出了一個(gè)關(guān)于解決滾動(dòng)時(shí)間跨度為標(biāo)準(zhǔn)的動(dòng)態(tài)PDPTW的方法。當(dāng)人們被分配到一輛新車(chē)時(shí),優(yōu)先考慮決策思維對(duì)于短期或者長(zhǎng)期投入的影響。這樣一來(lái),能夠更好地管理分散時(shí)間段便于降低路線(xiàn)成本。另一方面,橋本龍?zhí)傻?(2007年),使用本地搜索來(lái)確定車(chē)輛的行駛路線(xiàn)。在評(píng)估一個(gè)配送中心的解決方案時(shí),他們計(jì)算出了各條路線(xiàn)的最佳時(shí)