用多个配送中心来建立城市配送模型解决配送问题外文翻译

1、用多个配送中心来建立城市配送模型解决配送问题外文翻译 外文翻译原文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. 译文用多个配送中心来建立城市配送模型解决配送问题 资料来源: Netw Spat 经济周刊作者:大卫 伊苏卡隆 随着时间的推移,由于城市人口的大量增加,由市区货物配送所产生的问题也越来越复杂,其原因可归结于交通事故,交通

38、堵塞,非法泊车,准时交货,时间的限制,电子商务,其中最重要的是污染现象对于环境的影响。虽然如今关于解决线路和调度问题的文献是非常全面的,但是几乎没有任何成型的模式存在,考虑到其关键性,从研究的角度来看,它仍然需要寻找合适的方法来解决上述问题所造成的负面影响,通过运用一个新的策略和方法进行分析。 本文的目的是在大城市中模拟城市配送车辆行驶线路。集线器是一本非常有名的文献,它往往应用在许多调度问题和战略模式方面,如空气流量模型,物流模型等,在过去的几年里,新的配送中心(称为城市配送中心,U DCs或DCs)已经出现在城市中。芬尼根等人(2005年),在都柏林市中心实施了一项有关可持续货物配送的研究

39、,尤其关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货物和货物包装存放的缓冲区,这是货物在被传递到商店和企业前,可以进行预先储存的地方。在这些配送中心,将会出现类似于相应的路线分布的问题。 这些配送中心的主要目标之一是减少交通拥堵(都是由于街上的货车过多,因为它不可能产生足够的停车位),在配送区域内的问题,例如非法泊车导致交通流量减少。由于商店和企业要求的交货时间越来越短,物流配送车辆的调度成为了分销商迫切需要解决的问题。人们认识到,传统体制下的固定配送路线已经不能满足贸易的期望,因为在某些情况下,分销商是非常低效的。 在这项工作中,新的车辆路线模型(基于已知的时间依赖

40、型车辆路线问题的时间表,TDVRPTW,休伊阔等。2006年)已经制定,并且在传统方法上进行了改变,提出采用统一的系统,由城市配送中心为其中一些客户提供服务(更丰富的的服务项目,例如,混合动力汽车),而剩下的客户是由传统路线提供服务。这项研究是根据实时交通数据采集系统所开展出来的,其目的和国家与国际政策的一样,在于降低大气中排放的温室气体浓度。 由于商店在城市中心区与郊区的分布密度差别是很大的,因此并不是所有的商店都能通过配送中心来提供服务。出于这个原因,配送中心应该设在一个商店和人口高度集中的区域,通过传统交付作出直接分配。 采用的方法应该进一步考虑延长传统VRPTW模型对于总交付成本和到达

41、时间在每个区域内的影响。 本文结构如下:在该段介绍后面,将会介绍一个时间依赖模型,然后将模型的制定分为两部分,分别是数学模型的描述和介绍。在介绍了这个模型后将是本文的重点既解决算法,解释了何为最快出发时间。该解决方案的过程总体显示为良好。本文的最后部分,即案例研究,涉及到药品徐徐求量的分布情况,以及相关的计算方法和计算结果。最后,讨论了一些研究结果和未来所需要做的工作。 在描述新的模型之前,简要介绍一下时间依赖型车辆关于路径问题的(TDVRP)一般概念。这是一个没有必要进行解释的VRP模型,因为它已经被广泛应用了。 时间依赖型的车辆路径问题(TDVRP),是另一种经典的车辆路径问题的变型,包括

42、在固定时间内制定最佳配送路线的问题,车队在一天时间内,从它的始发地出发。事实上,在城市环境中,可变交通条件发挥着重要的作用,如果要实现优化,这是我们不能忽视的方面。一种合理的优化方法包括安排,规划和寻找解决办法,其目的在于最大限度地减少三个层次目标:路线,总行程时间和成本数。 米特罗维奇-铭尼科等(2004年)提出了一个关于解决滚动时间跨度为标准的动态PDPTW的方法。当人们被分配到一辆新车时,优先考虑决策思维对于短期或者长期投入的影响。这样一来,能够更好地管理分散时间段便于降低路线成本。另一方面,桥本龙太郎等 (2007年),使用本地搜索来确定车辆的行驶路线。在评估一个配送中心的解决方案时,他们计算出了各条路线的最佳时