快遞分揀和配送外文文獻(xiàn)翻譯最新譯文

1、文獻(xiàn)出處：Ferrucci F, Bock S. Real-time control of express pickup and delivery processes in a dynamic environment [J]. Transportation Research Part B: Methodological, 2014, 63: 1-14.原文 原文Real-time control of express pickup an

2、d delivery processes in a dynamic environmentFrancesco Ferrucci ；Stefan Bock1. IntroductionDaily transportation services of express courier service companies are characterized by a highly dynamic environment in which the

3、 system situation frequently changes by the occurrence of various dynamic events. A key characteristic is that dynamically arriving requests have to be transported from pickup locations to delivery locations on the same

4、day. Since it is highly desired that requests are fulfilled within given time windows, transportation activities are often carried out under high time pressure. Moreover, road networks are frequently congested and unreli

5、able. Consequently, besides the arrival of new requests, traffic congestion and vehicle disturbances, i.e., slowdowns and breakdowns, have to be managed in real-time. Thanks to advances in information and communication t

6、echnologies, information about dynamic events which is only available during the execution of the transportation service can now be utilized ( Larsen, 2000 and Giaglis et al., 2004).1.1. ContributionsIn this paper, we pr

7、opose a new real-time control approach for efficiently coordinating dynamic transportation services of express courier service companies. In order to provide practical decision support, this approach is based on an exten

8、ded Dynamic Pickup and Delivery Problem (DPDP) that integrates various sources of dynamic events as well as several real-world aspects. We denote this new variant as the Dynamic Pickup and Delivery Problem with Real-Time

9、 Control (DPDPRC). It is specifically designed in order to efficiently control urgent real-world transportation services which are executed by express courier service companies. The main contributions of this paper are:T

10、he considered transportation services can be modeled as a variant of the Pickup and Delivery Problem (PDP) which is a generalization of the well-studied Vehicle Routing Problem (VRP, see Toth and Vigo, 2002 and Golden et

11、 al., 2008) and a special case of the General Pickup and Delivery Problem (GPDP, see Savelsbergh and Sol, 1995). Variants of PDPs have become a vital research area because of their practical relevance. A closely related

12、problem that focuses on passenger transportation is the Dial-a-Ride Problem (DARP, see Cordeau and Laporte, 2007, Cordeau et al., 2007, Paquette et al., 2013 and Kirchler and Wolfler Calvo, 2013). In the DARP, additional

13、 driving constraints and convenience objectives are considered.In the literature, approaches for static PDPs are distinguished from dynamic concepts. In approaches for static PDPs it is assumed that the problem data is k

14、nown in advance with certainty (see, e.g., Nanry and Wesley Barnes, 2000, Lu and Dessouky, 2004 and Bard and Jarrah, 2009). Hence, on account of the absence of dynamic events, no plan adaptation is necessary during the e

15、xecution of the transportation service. In contrast, real-time concepts can handle unexpected changes of the system situation caused by dynamic events (see Ghiani et al., 2003, Mitrovic-Minic et al., 2004, Mitrovic-Minic

16、 and Laporte, 2004 and Fabri and Recht, 2006). With regard to the focus of this paper, only real-time approaches are described in what follows. An overview about dynamic PDPs can be found in Berbeglia et al. (2010).While

17、 most approaches consider the arrival of new requests, other sources of dynamic events are also considered in selected research work. Modeling of traffic congestion is considered in the work of Fleischmann et al., 2004,

18、Attanasio et al., 2007, Barceló et al., 2007, Haghani and Yang, 2007, Cortés et al., 2008 and Bock, 2010. Moreover, vehicle disturbances are considered in Li et al., 2009, Li et al., 2009, Bock, 2010 and Mu et

19、al., 2010.Recently, there have been a number of approaches that use stochastic knowledge about expected future request arrivals. While most approaches deal with dynamic VRPs (see, e.g., Bent and van Hentenryck, 2004, Ich