Ensuring service levels in routing problems with time windows and stochastic travel times

In the stochastic variant of the vehicle routing problem with time windows, known as the SVRPTW, travel times are assumed to be stochastic. In our chance-constrained approach to the problem, restrictions are placed on the probability that individual time window constraints are violated, while the objective remains based on traditional routing costs. In this paper, we propose a way to offer this probability, or service level, for all customers. Our approach carefully considers how to compute the start-service time and arrival time distributions for each customer. These distributions are used to create a feasibility check that can be “plugged” into any algorithm for the VRPTW and thus be used to solve large problems fairly quickly. Our computational experiments show how the solutions change for some well-known data sets across different levels of customer service, two travel time distributions, and several parameter settings.     

A priori policy evaluation and cyclic-order-based simulated annealing for the multi-compartment vehicle routing problem with stochastic demands

We develop methods to estimate and exactly calculate the expected cost of a priori policies for the multi-compartment vehicle routing problem with stochastic demands, an extension of the classical vehicle routing problem where customer demands are uncertain and products must be transported in separate partitions. We incorporate our estimation procedure into a cyclic-order-based simulated annealing algorithm, significantly improving the best-known solution values for a set of benchmark problems. We also extend the updating procedure for a cyclic order’s candidate route set to duration-constrained a priori policies.     

Hierarchical routing over dynamic wireless networks

The topology of a mobile wireless network changes over time. Maintaining routes between all nodes requires the continuous transmission of control information, which consumes precious power and bandwidth resources. Many routing protocols have been developed, trading off control overhead and route quality. In this paper, we ask whether there exist low‐overhead schemes that produce low‐stretch routes, even in large networks where all the nodes are mobile. We present a scheme that maintains a hierarchical structure within which constant‐stretch routes can be efficiently computed between every pair of nodes. The scheme rebuilds each level of the hierarchy periodically, at a rate that decreases exponentially with the level of the hierarchy. We prove that this scheme achieves constant stretch under a mild smoothness condition on the nodal mobility processes. Furthermore, we prove tight bounds for the network‐wide control overhead under the additional assumption of the connectivity graph forming a doubling metric space. Specifically, we show that for a connectivity model combining the random geometric graph with obstacles, constant‐stretch routes can be maintained with a total overhead of bits of control information per time unit. © 2015 Wiley Periodicals, Inc. Random Struct. Alg., 47, 669–709, 2015     

Controllable wettability of laser treated aluminum mesh for on-demand oil/water separation

Oil/water separation has attracted more attention with the dramatic increasing of oil spill accidents and arbitrarily discharged oily industrial water. However, many reported materials with controllable wettability for on-demand oil/water separation of both heavy and light oil/water mixtures involve complicated devices and dangerous fabrication processes. Herein, we propose a simple, environmentally friendly and high-efficient method to fabricate Al mesh with controllable wettability. Heavy oil can be separated with a high efficiency of 99% in oil-removing mode. For light oil, the separation efficiency can also reach up to 99% in water-removing mode. Additionally, surface wettability of the mesh can be conversed from superhydrophobicity to superhydrophilicity by atmospheric pressure plasma jet (APPJ) and heating, thereby realizing continuous bidirectional separation. Therefore, this work provides a facile, green, and efficient way for on-demand oil/water separation and finds a promising solution for oil pollution problems.     

有时间窗的车辆路径问题及改进禁忌搜索算法

基于改进的禁忌搜索算法求解有时间窗的车辆路径问题,建立了该问题的通用数学模型.改进算法中,在随机构造的多个可行解中挑选较好的解作为初始解,采用2-opt方法生成邻域,并构造了动态禁忌表,使禁忌表的大小和结构随搜索过程发生改变,提高了整体寻优能力.仿真实验证明了算法的可行性、有效性和优越性.     

基于多目标的管道物联网无线路由算法

在恶劣的环境下传感器节点能量限制一直是制约油气管道物联网性能的关键因素.网络端对端延时决定了油气管道物联网对于管道安全事故的反应时间.为此,针对油气管道物联网能量限制和端对端延时问题提出基于多目标优化的管道物联网无线路由算法,通过将节点剩余能量以及节点到汇聚节点之间的距离作为机会路由中选择候选转发节点的指标,实现了物联...     

求解车辆路径问题的改进遗传算法

在建立车辆路径问题数学模型的基础上,设计了求解该问题的改进遗传算法,即采用自然数编码,构造一定长度的遗传个体表,动态记录适应度以及引入新交叉算子。实验结果表明,该算法用于求解车辆路径问题,不但可以解决传统遗传算法在求解该问题所遇到的“早熟收敛”,而且大大提高算法的运行效率。     

基于蚁群的无线传感器网络概率路由算法

针对多数无线传感器网络路由算法易在网络中形成关键节点,而节点的失效往往导致整个网络的失效问题,提出了将随机思想与蚁群算法的特征相结合的一种新的概率路由计算方法.实验表明,该算法对延长整个网络的有效生存时间的效果较好.     

一种能量高效的无线传感器网络分簇路由算法

分析了无线传感器网络的分簇路由算法,针对现有算法存在的热点问题,提出一种基于分簇思想的能量高效路由算法.采用簇首轮转及局部竞争优化节点簇内通信的能量消耗,采用粒子群优化算法均优化簇首节点的簇间通信负载和能量消耗,从而延长网络的生命期.仿真结果表明,该算法能够有效提高无线传感器网络生存期以及节点与网络的能量利用率.     

Ad Hoc网络NLRP路由协议及其开销函数

目的 研究移动Ad Hoc网络路由协议的规模性开销函数。方法 运用所提出的节点位置路由协议(NLRP,Node Location Routing Protocol)和节点移动性分析模型,推导了与位置更新和目的节点搜索有关的开销函数。结果 路由协议的总开销是凸函数,最佳位置更新阈值决定了路由开销。结论 对于给定的路由协议,网络的规模性取决于路由开销。根据路由请求到达的分布规律和节点的移动性,建立协议的开销函数,是进行网络优化和规模性研究的关键。