A deterministic tabu search algorithm for the fleet size and mix vehicle routing problem

The fleet size and mix vehicle routing problem consists of defining the type, the number of vehicles of each type, as well as the order in which to serve the customers with each vehicle when a company has to distribute goods to a set of customers geographically spread, with the objective of minimizing the total costs. In this paper, a heuristic algorithm based on tabu search is proposed and tested on several benchmark instances. The computational results show that the proposed algorithm produces high quality results within a reasonable computing time. Some new best solutions are reported for a set of test problems used in the literature.     

A Guided Tabu Search for the Vehicle Routing Problem with two-dimensional loading constraints

We present a metaheuristic methodology for the Capacitated Vehicle Routing Problem with two-dimensional loading constraints (2L-CVRP). 2L-CVRP is a generalisation of the Capacitated Vehicle Routing Problem, in which customer demand is formed by a set of two-dimensional, rectangular, weighted items. The purpose of this problem is to produce the minimum cost routes, starting and terminating at a central depot, to satisfy the customer demand. Furthermore, the transported items must be feasibly packed into the loading surfaces of the vehicles. We propose a metaheuristic algorithm which incorporates the rationale of Tabu Search and Guided Local Search. The loading aspects of the problem are tackled using a collection of packing heuristics. To accelerate the search process, we reduce the neighbourhoods explored, and employ a memory structure to record the loading feasibility information. Extensive experiments were conducted to calibrate the algorithmic parameters. The effectiveness of the proposed metaheuristic algorithm was tested on benchmark instances and led to several new best solutions.     

A variable neighbourhood search algorithm for the open vehicle routing problem

In the open vehicle routing problem (OVRP), the objective is to minimise the number of vehicles and then minimise the total distance (or time) travelled. Each route starts at the depot and ends at a customer, visiting a number of customers, each once, en route, without returning to the depot. The demand of each customer must be completely fulfilled by a single vehicle. The total demand serviced by each vehicle must not exceed vehicle capacity. Additionally, in one variant of the problem, the travel time of each vehicle should not exceed an upper limit.     

A unified exact method for solving different classes of vehicle routing problems

This paper presents a unified exact method for solving an extended model of the well-known Capacitated Vehicle Routing Problem (CVRP), called the Heterogenous Vehicle Routing Problem (HVRP), where a mixed fleet of vehicles having different capacities, routing and fixed costs is used to supply a set of customers. The HVRP model considered in this paper contains as special cases: the Single Depot CVRP, all variants of the HVRP presented in the literature, the Site-Dependent Vehicle Routing Problem (SDVRP) and the Multi-Depot Vehicle Routing Problem (MDVRP). This paper presents an exact algorithm for the HVRP based on the set partitioning formulation. The exact algorithm uses three types of bounding procedures based on the LP-relaxation and on the Lagrangean relaxation of the mathematical formulation. The bounding procedures allow to reduce the number of variables of the formulation so that the resulting problem can be solved by an integer linear programming solver. Extensive computational results over the main instances from the literature of the different variants of HVRPs, SDVRP and MDVRP show that the proposed lower bound is superior to the ones presented in the literature and that the exact algorithm can solve, for the first time ever, several test instances of all problem types considered.      

A powerful route minimization heuristic for the vehicle routing problem with time windows

We suggest an efficient route minimization heuristic for the vehicle routing problem with time windows. The heuristic is based on the ejection pool, powerful insertion and guided local search strategies. Experimental results on the Gehring and Homberger’s benchmarks demonstrate that our algorithm outperforms previous approaches and found 18 new best-known solutions.     

基于无线Mesh网络的一种信道分配算法及路由协议

提出了在多信道环境下的无线Mesh网络中的一种混合型路由协议TOIRP(tree-based and on-de-mand integrated routing protocol)以及一种分布式的信道分配算法CLBCA(channel load based channel assign-ment).TOIRP协议采用HWMP(hybrid wireless mesh protocol)所提出的混合路由技术,将基于树的路由与传统的AODV(ad hoc on-demand distance vector)路由相结合,减少路由发现的时延,同时采用了一种新的路由判据CETTI(cumulative expected transmission time with interference).该路由判据充分考虑多信道的特性,设计了一种量化通信干扰的方法,将干扰分为外部数据流对路径的干扰以及路径内部数据流的干扰两个方面,并综合考虑了跳数、时延等因素,提高了网络的吞吐量.信道分配算法分为收发器与邻居节点绑定和收发器与信道绑定两个部分,将信道的负载作为选择信道的标准,避免了多信道中常见的信道依赖所造成的影响,并且提高了信道的利用率.模拟结果表明,采用新的路由判据后,网络的吞吐量最优情况下得到提升.     

改进蚁群算法优化周期性车辆路径问题

周期性车辆路径问题(PVRP)是标准车辆路径问题(VRP)的扩展,PVRP将配送期由单一配送期延伸到T(T＞1)期,因此,PVRP需要优化每个配送期的顾客组合和配送路径。由于PVRP是一个内嵌VRP的问题,其比标准VRP问题更加复杂,难于求解。本文采用蚁群算法对PVRP进行求解,并提出采用两种改进措施——多维信息素的运用和基于扫描法的局部优化方法来提高算法的性能。最后,通过9个经典PVRP算例对该算法进行了数据实验,结果表明本文提出的改进蚁群算法求解PVRP问题是可行有效的,同时也表明两种改进措施可以显著提高算法的性能。     

无线传感器网络中基于网络编码的容错路由

针对无线传感器网络中节点被窃听和盗用对数据安全传输所带来的影响,提出了一种基于网络编码的容错路由(fault-tolerant routing based on network coding,FR-NC).该路由算法利用网络中大多数节点能正确传输数据的特点,通过选举保证数据一致性,从而防止了盗用节点对数据的篡改;同时对随机编码系数进行加密,起到了对数据安全的监督和保护作用.通过对实验结果的分析,可以发现当网络中存在一定数量的盗用节点时,FR-NC具有较好的健壮性.     

水下通信中的异常声压监控网络系统设计

传统水下通信声压异常监控网络存在无法自主完成节点的投放和回收,存储监控盲区并且无法进行动态组网,不能对异常声压进行准确的监控等较大的缺陷;为此,设计并实现了一种新的水下异常声压监控系统,系统中的通信协议基于节点间的深度信息完成数据的转发,给出了系统中监控器、CC2430 处理器、终端节点以及协调器节点的硬件设计原理并给出了系统采集数据的软件流程;系统中实现了对链路层的AODV 路由协议进行改进,增强系统对异常声压的监控性能;测试结果说明,该系统获取的声压监测星座图明显优于传统系统,在不同的干扰类型下,发射信号使用PSK调制,载波中心频率是10 kHz,采样率是50 kHz,码率是2 000 bit/s;实验结果表明:该种系统具有较低异常声压信号监控误差率,可对异常声压信道的传输特性进行较好的校正和补偿,具有较强稳定性。