基于定位辅助按需拓扑维护的超宽带自组网路由算法

提出了一种基于定位辅助按需拓扑维护的超宽带自组网路由算法,该算法利用超宽带技术精确定位信息所获得的网络拓扑信息和路由信息进行分组转发,路由维护阶段在定位信息辅助下采用按需方式进行断链路由的修复和拓扑维护,通过基于位置信息的按需路由发现和限制路由查找范围,以及定位信息和网络拓扑信息的及时更新,在降低协议开销的同时保证了算法的有效性。仿真表明,该算法在分组丢失率、平均端到端时延和路由附加开销等方面具有良好性能,其优良的分布式控制特征能适应超宽带自组网的动态环境。     

模块化与我国轨道运输装备的技术创新

通过技术引进和自主创新，快速提升我国轨道运输装备水平，是实现铁路客运高速、快速和货运快捷、重栽的关键。产业组织是实现有效的技术引进和自主创新的基础，模块化产业组织有利于模块化轨道运输装备的发展，有利于整车和模块化部件的创新。发达国家模块化的轨道运输装备产业组织有力地促进了模块化的轨道运输装备的创新与发展，模块化轨道运输装备产品对我国既有一体化的产业组织提出了挑战，本文提出模块化的产业组织是我国轨道运输装备制造业的发展方向。     

从喻体和喻义看英汉比喻的文化差异

比喻性习语在英汉语言中大量存在,但由于两种语言反映的文化不同,使得英汉习语在比喻形象的运用上存在明显差异。文章介绍和比较了三种喻体在各自习语中的使用情况,并提出只有了解和掌握英汉比喻中的这种文化差异,才能在跨文化交际时准确无误地传递隐含在语言里的文化信息。     

一种基于MPLS业务量工程的选路机制

分析了诸如受限路由等传统QoS路由机制业务震荡现象出现的原因给出了呼叫级QoS路由和分组级QoS路由的概念在此基础上提出了多标签QoS路由机制(MLR)作为一种分组级QoS路由机制多标签QoS路由机制不仅能够从理论上避免业务震荡现象的出现同时由于采用了业务量工程的业务均衡的思想从而提高了全网的业务性能指标仿真的数据结果可以在同时运行实时业务和非实时业务下得到     

Pareto mimic algorithm: An approach to the team orienteering problem

The team orienteering problem is an important variant of the vehicle routing problem. In this paper, a new algorithm, called Pareto mimic algorithm, is proposed to deal with it. This algorithm maintains a population of incumbent solutions which are updated using Pareto dominance. It uses a new operator, called mimic operator, to generate a new solution by imitating an incumbent solution. Furthermore, to improve the quality of a solution, it employs an operator, called swallow operator which attempts to swallow (or insert) an infeasible node and then repair the resulting infeasible solution. A comparative study supports the effectiveness of the proposed algorithm, especially, our algorithm can quickly find new better results for several large-scale instances. We also demonstrate that Pareto mimic algorithm can be generalized to solve other routing problems, e.g., the capacitated vehicle routing problem.     

Flexible work planning of service agents with load balancing

This work emerged from the need to better plan the daily work of 29 travelling service agents, who provide 1090 services to 412 customers in 283 sites, on daily average. A handy and flexible tool was developed and is presented herein. A major contribution of this study is an explicit consideration of the multi-dimensional nature of the problem by the inclusion of workload balancing, which may stand in conflict to cost minimisation. Further, the geographical distribution of the demand is highly irregular. Therefore, two load measures are required and balanced. This required to fitting a proper planning scheme. The planning tool has been applied successfully by the commercial service provider. Improvements in the order of 20% and more were obtained in key performance measures. Moreover, cost reductions, service improvement and load balance were obtained simultaneously: the standard deviations of the service times and working day’s duration were reduced by 18 and 58%, respectively. This enables to reduce the number of agents with no significant harm in performance. Additional practical advantages of the proposed tool are also discussed and demonstrated, for example, the ability to cope with geographical distributions and the flexibility to respond to daily variations in demand.     

基于改进量子进化算法的车货供需匹配方法研究

为了提高货运供需匹配效率,建立了一种车货供需匹配数学模型,描述了车货匹配问题的目标与相关约束,对量子进化算法进行设计与改进用于对此问题求解,提出了有约束惩罚的适应度衰减方法,解决了量子群初期无强可行解时最优量子个体的选择问题,引入量子群成熟度对量子进化算法的退出机制进行改进。在实验中,使用改进的量子进化算法和标准遗传进化算法进行对比,并对算法参数进行优化,实验中量子进化算法表现出更好的收敛速度,准确性和稳定性,但是量子群规模存在“瓶颈问题”,更大规模的量子群对算法优化效果并不明显且需要耗费更长的计算机时间,量子旋转角增量与算法收敛速度正相关,与全局搜索能力负相关。结果表明,改进的量子进化算法可以高效地搜索到较为优秀的车货匹配方案,为车主和货主推荐较为合理的车货供需信息资源。     

考虑消费者预期的电动汽车分时租赁市场价格竞争模型

分时租赁平台作为电动汽车推广的主要方式,其特征与打车软件类似,在风险资本的推动下极易引发价格战。各租车公司的市场需求量不仅与自己的定价有关,也与竞争对手的定价策略相关,目标都是各自利润的最大化。本文在考虑消费者预期的基础上,研究了需求函数为线性情形下的多人博弈,证明了此博弈是超模博弈以及Nash均衡的存在性和唯一性。并进一步揭示了降价幅度、交叉价格和价格敏感消费群体占比对均衡价格、均衡需求量和利润的影响关系,讨论了价格竞争过程中各租车公司的决策过程与利弊关系。结果表明:任意租车公司的降价行为都会引发整个市场的降价反应,且降价幅度随着博弈阶段的推进逐渐减小,最终收敛于均衡价格;动态定价博弈存在最优组合策略,市场竞争时应当把握好降价幅度,避免过度的价格竞争;均衡价格是关于消费者预期的单调减函数,价格敏感的消费群体占比越大,租车公司间价格竞争越激烈,降价幅度会越大,均衡价格越低;对于市场份额大的租车公司利润是关于价格敏感型消费者占比的单调增函数,但对中小租车公司而言则是单调减函数,价格敏感的消费者越多,对大公司有利,对中小公司不利。     

基于ASRank和MMAS的蚁群算法求解飞机指派问题

本文将航班串的飞机指派问题归结为车辆路径问题,考虑连续航班串之间衔接时间、衔接机场的约束、每架飞机的总飞行时间约束,建立了带有飞行时间约束的车辆路径问题的混合整数规划模型。构造了蚁群系统算法,引入基于排序的蚂蚁系统和最大最小蚂蚁系统算法的信息素更新策略。选取某航空公司7组初始航班串集合进行测试,并对算法中的重要参数进行了分析。实验结果表明,本文设计的模型和算法可以有效地减少连续航班串之间的总衔接时间,在可接受的计算时间内获得满意解。     

An investigation into the vehicle routing problem with time windows and link capacity constraints

In this work, we investigate a new, yet practical, variant of the vehicle routing problem called the vehicle routing problem with time windows and link capacity constraints (VRPTWLC). The problem considers new constraints imposed on road links with regard to vehicle passing tonnage, which is motivated by a business project with a Hong Kong transportation company that transports hazardous materials (hazmats) across the city and between Hong Kong and mainland China. In order to solve this computationally challenging problem, we develop a tabu search heuristic with an adaptive penalty mechanism (TSAP) to help manage the company's vehicle fleet. A new data set and its generation scheme are also presented to help validate our solutions. Extensive computational experiments are conducted, showing the effectiveness of the proposed solution approach.