基于第三方物流的家具配送开放式车辆路径问题

为了降低家具配送成本,提高物流效率,基于第三方物流配送模式,构建了以总行驶距离最短和车辆数最少为最优目标的开放式车辆路径问题(open vehicle routing problem,OVRP)数学模型,并设计了一个改进的两阶段禁忌搜索算法进行求解,第1阶段求解包含所有客户的TSP(traveling salesman problem)路径来作为第2阶段划分OVRP路径的基础.设计了一个随机动态禁忌表,并将"邻域算子编号"和"邻域交换点对"同时作为禁忌对象,避免了过度禁忌的情况.另外,对5个邻域算子进行了测试,表明采用由点交换、分序点插入、点逆序和前点前向插入这4个算子组成的多邻域结构体效果最佳.经算例测试和文献对比,验证了设计算法的有效性,采用第三方物流配送比自营物流配送更节省成本.     

基于SDN的互联网域间路由研究

互联网流量的爆发式增长,叠加互联网流量固有的突发性特点,使得网络流量不均衡现象日益加剧。传统BGP协议由于缺乏全网拓扑和全局流量观,只能遵循标准BGP选路原则,在解决流量调度和负载均衡方面存在不足。针对BGP协议存在的局限性,研发了基于RR+的互联网骨干网流量调度系统,并应用于ChinaNet骨干网的网内中继、网间互联出口、IDC出口等多个流量优化场景。更进一步地,提出了一种基于SDN的互联网域间路由架构,通过在域间控制器之间交换BGP路由,无需在域内和域间运行BGP协议,极大地简化了网络协议,并能够实现灵活的流量调度和负载均衡。     

A variable neighborhood search heuristic algorithm for the double vehicle routing problem with multiple stacks

This paper addresses the double vehicle routing problem with multiple stacks (DVRPMS) in which a fleet of vehicles must collect items in a pickup region and then travel to a delivery region where all items are delivered. The load compartment of all vehicles is divided into rows (horizontal stacks) of fixed profundity (horizontal heights), and on each row, the unloading process must respect the last‐in‐first‐out policy. The objective of the DVRPMS is to find optimal routes visiting all pickup and delivery points while ensuring the feasibility of the vehicle loading plans. We propose a new integer linear programming formulation, which was useful to find inconsistencies in the results of exact algorithms proposed in the literature, and a variable neighborhood search based algorithm that was able to find solutions with same or higher quality in shorter computational time for most instances when compared to the methods already present in the literature.     

基于ARMA模型的双路径差异性分析

拟通过单向时延的历史记录对其未来趋势进行预测。首先,通过粗粒度和细粒度两种方式采集世界各地若干目标节点的单向时延作为原始数据;然后,结合多种预测模型的特点和原始数据的内在属性,提出一种基于ARMA模型的双路径差异性分析方法;最后选取合理的预测窗口对方法的准确性进行验证。结果表明,该预测方法是正确、合理的,与灰色预测模型相比能更有效地预测单项时延差序列。     

Comprehensive performance evaluation of distributed and dynamic mobility routing strategy

In this paper, we conduct a comprehensive performance study of distributed and dynamic mobility management (DDMM). DDMM presents a new architectural paradigm for a sustainable mobile networking against an ever-increasing amount of Internet data traffic, providing IP mobility management with distributed deployment of mobility anchors and dynamic activation when mobility is needed. Such a distributed mobility management concept is generally and intuitively accepted in terms of effective distribution of mobile traffic when compared with centralized mobility management (CMM) approaches. Nevertheless, the routing strategy of DDMM has not yet been properly examined through performance studies, and especially the impact of potential mobility routing strategies on the user plane is an open question. We perform a mathematical analysis of DDMM and present numerical results aiming to identify in which conditions, by which factors, and how much, DDMM improves mobility performance. For comparison, Mobile IPv6, Proxy Mobile IPv6 (PMIPv6), and PMIPv6 localized routing (PMIPv6-LR) were considered as representative IP mobility protocols following CMM approaches. Analytical results demonstrate that DDMM generally achieves higher performance when compared with CMM-based protocols in terms of packet delivery cost, tunneling overhead, and throughput, but specific performance varies in function of multiple input parameters.     

基于三维胞元空间的MA双向并行路由算法

针对传统移动代理(MA)在监测无线传感器网络(WSNs)的感兴趣信息时产生的延迟较大和能耗较多问题,提出了基于三维胞元空间的MA双向并行(3D-BPMA)路由算法.3D-BPMA将MA与传统的客户/服务器(c/S)模式相结合,在胞元内利用C/S模式搜集信息,在单层胞元系统和路由器与路由器之间采用MA双向并行的策略进行传输.仿真结果表明:3D-BPMA与LCF,DSG-MIP算法相比减少了平均响应时间和网络平均能耗,提高了MA发送率.     

Testing local search move operators on the vehicle routing problem with split deliveries and time windows

The vehicle routing problem (VRP) is an important transportation problem. The literature addresses several extensions of this problem, including variants having delivery time windows associated with customers and variants allowing split deliveries to customers. The problem extension including both of these variations has received less attention in the literature. This research effort sheds further light on this problem. Specifically, this paper analyzes the effects of combinations of local search (LS) move operators commonly used on the VRP and its variants. We find when paired with a MAX-MIN Ant System constructive heuristic, Or-opt or 2-opt⁎ appear to be the ideal LS operators to employ on the VRP with split deliveries and time windows with Or-opt finding higher quality solutions and 2-opt⁎ requiring less run time.     

Customer satisfaction in dynamic vehicle routing problem with time windows

The dynamic vehicle routing and scheduling problem is a well-known complex combinatorial optimization problem that drew significant attention over the past few years. This paper presents a novel algorithm introducing a new strategy to integrate anticipated future visit requests during plan generation, aimed at explicitly improving customer satisfaction. An evaluation of the proposed strategy is performed using a hybrid genetic algorithm previously designed for the dynamic vehicle problem with time windows that we modified to capture customer satisfaction over multiple visits. Simulations compare the value of the revisited algorithm exploiting the new strategy, clearly demonstrating its impact on customer satisfaction level.     

Heuristic algorithms for a three-dimensional loading capacitated vehicle routing problem in a carrier

In this paper, we present heuristic algorithms for a three-dimensional loading capacitated vehicle routing problem arising in a real-world situation. In this problem, customers make requests of goods, which are packed in a sortment of boxes. The objective is to find minimum cost delivery routes for a set of identical vehicles that, departing from a depot, visit all customers only once and return to the depot. Apart of the usual 3D container loading constraints which ensure that the boxes are packed completely inside the vehicles and that the boxes do not overlap each other in each vehicle, the problem also takes into account constraints related to the vertical stability of the cargo and multi-drop situations. The algorithms are based on the combination of classical heuristics from both vehicle routing and container loading literatures, as well as two metaheuristic strategies, and their use in more elaborate procedures. Although these approaches cannot assure optimal solutions for the respective problems, they are relatively simple, fast enough to solve real instances, flexible enough to include other practical considerations, and normally assure relatively good solutions in acceptable computational times in practice. The approaches are also sufficiently generic to be embedded with algorithms other than those considered in this study, as well as they can be easily adapted to consider other practical constraints, such as the load bearing strength of the boxes, time windows and pickups and deliveries. Computational tests were performed with these methods considering instances based on the vehicle routing literature and actual customers’ orders, as well as instances based on a real-world situation of a Brazilian carrier. The results show that the heuristics are able to produce relatively good solutions for real instances with hundreds of customers and thousands of boxes.     

An adaptive local search algorithm for vehicle routing problem with simultaneous and mixed pickups and deliveries

The Vehicle Routing Problem with Simultaneous Pickup and Delivery (VRPSPD) is an extension to the classical Vehicle Routing Problem (VRP), where customers may both receive and send goods simultaneously. The Vehicle Routing Problem with Mixed Pickup and Delivery (VRPMPD) differs from the VRPSPD in that the customers may have either pickup or delivery demand. However, the solution approaches proposed for the VRPSPD can be directly applied to the VRPMPD. In this study, an adaptive local search solution approach is developed for both the VRPSPD and the VRPMPD, which hybridizes a Simulated Annealing inspired algorithm with Variable Neighborhood Descent. The algorithm uses an adaptive threshold function that makes the algorithm self-tuning. The proposed approach is tested on well-known VRPSPD and VRPMPD benchmark instances derived from the literature. The computational results indicate that the proposed algorithm is effective in solving the problems in reasonable computation time.