A comparative study between dynamic adapted PSO and VNS for the vehicle routing problem with dynamic requests

Combinatorial optimization problems are usually modeled in a static fashion. In this kind of problems, all data are known in advance, i.e. before the optimization process has started. However, in practice, many problems are dynamic, and change while the optimization is in progress. For example, in the dynamic vehicle routing problem (DVRP), new orders arrive when the working day plan is in progress. In this case, routes must be reconfigured dynamically while executing the current simulation. The DVRP is an extension of a conventional routing problem, its main interest being the connection to many real word applications (repair services, courier mail services, dial-a-ride services, etc.). In this article, a DVRP is examined, and solving methods based on particle swarm optimization and variable neighborhood search paradigms are proposed. The performance of both approaches is evaluated using a new set of benchmarks that we introduce here as well as existing benchmarks in the literature. Finally, we measure the behavior of both methods in terms of dynamic adaptation.     

A preliminary study of a diagonal channel-routing model

The layout of two-terminal nets in a VLSI channel is realized in a new diagonal channel-routing model (DCRM), where the tracks are segments respectively displayed at +45 ° and –45 ° on the two layers of the channel. A new definition of channel density is introduced, and a lower bound to the channel width is derived by the application of an algorithm, whose complexity is evaluated as a function of the channel density, and other parameters of the problem.A simple linear-time algorithm is proposed, which produces an optimal layout (i.e., it requires a channel of minimum width) if the length of the longest net equals the lower bound for the channel width. In any case, the number of vias is at most one for each net. Some particular solutions are proposed for problems with long nets.Specific problems are much easier in DCRM than in the classical Manhattan model. For example, any shift-by-i can be realized in DCRM in a channel of widthi.This work has been supported by Consiglio Nazionale delle Ricerche of Italy under a research grant.     

改进的蚁群算法在飞行路径模型中的应用

为了保障飞机安全地运行,FAA规定每架飞机在飞行一定时间后都要进行周期性检修。通常考虑到检修成本,任一种检修都要在指定的机场完成,因此要求飞机每飞行一定的小时数后都要返回到指定的维护基地进行定期检修。如何合理地进行飞机飞行路径的调度以使飞机周期性地返回指定检修机场进行检修是本文研究的关键。为了问题简化,本文主要针对单检修基地、单机型的检修路径调度问题进行研究。本文结合经典蚁群算法,对现有算法参数的设置及信息的更新等方面进行改进后应用到飞行路径模型中,并运用Matlab对该算法编程,运用具体数据进行计算实现,确保了飞机周期性返回检修机场,实现周期性检修。     

基于种群多样性的自适应PSO算法求解VRPSPD问题

为有效求解逆向物流车辆路径(VRPSPD)模型,本文提出一种基于种群多样性的自适应PSO算法(SDAPSO)。在SDAPSO运行时,根据种群多样性,自适应地对种群中运行较差的粒子进行扰动操作,提升这些粒子向最优解收敛的能力;同时,对全局最优粒子进行概率扰动,以增加种群的多样性。标准检测函数的仿真结果表明SDAPSO算法是对基本PSO算法的有效改进。在对VRPSPD模型求解中,通过与其它粒子群算法相比,表明SDAPSO是求解该类问题的一种有效方法。     

一种无线链状网络路由算法的研究与应用

文章基于货运列车状态监控的无线传感器网络应用,针对网络节点能量有限以及链状网络节点负载不均衡的问题进行分析和研究,提出一种适合该应用的新型路由算法,该算法基于网络节点可通过功率控制来调整通信距离这一前提,为每个传感器节点选择合适的数据传输路径,以达到整个网络节省能耗,负载均衡的目的。仿真结果验证了该算法有效地平衡了网络负载,节省了网络能量,提高了网络生命周期。     

5G时代下的移动自组织网络探讨

移动自组织网络在高带宽低延时的5G下,赋予更多的技术优势,使其综合性、应用性以及系统性都得到有效的提高,本文从基于5G移动自组织网络展开探讨,论述移动自组织mesh的网络架构技术及其应用前景和未来趋势。     

无线传感器网络多路径路由协议研究进展*

在研究目前存在的多径路由协议特点及核心路由机制基础上,总结了多路径路由协议的特征,并对不同的多路径路由相关项进行了比较。最后指出了多路径路由的研究思路以及未来的发展趋势。     

基于连通度的Ad hoc网络路由协议研究与仿真*

对Ad hoc网络各种路由协议进行仿真评估,分析它们在不同约束条件下不同度量的相对性能,是了解与学习路由协议性能的重要手段.目前的度量标准主要集中在吞吐量、延时、抖动、丢包率等QoS因子或路由负载、寻路时间等外部特性上,还没有以Ad hoc网络系统本身的连通度作为度量标准进行仿真,评价各种路由协议在不同试验条件下对于同一网络系统连通度的影响的相关研究.基于能量模型、节点密度、停留时间及移动速率四种约束条件对MANET提出的四种路由协议进行了关于网络连通度的仿真与评估,给出了这方面的初步结论.     

无线自组网络中的基于多个支配集的路由协议*

提出了一种在无线自组网络中建立多个连通支配集,使其分时共同承担网络中继传输的方法,以防止部分节点被过度消耗,维持网络中能量消耗的平衡.仿真实验表明,基于多个连通支配集的路由方法可有效防止部分节点被过度消耗、维护网络的能量消耗平衡、延长网络的寿命.     

基于LIP和RSC的超立方体网络单播容错路由算法*

基于LIP和RSC的概念,提出了一个有效的超立方体网络单播容错路由算法.该算法不仅能容纳指数级的错误节点,而且算法效率也很高.