非冷链商品配送路径优化研究--以京东配送为例

如何有效降低商品配送成本是物流企业的关注重点,学界已就带时间窗的商品配送路径优化算法展开了相关研究,但相关算法还存在着过早陷入局部最优或无法收敛的问题。由此提出一种改进的变邻域遗传搜索算法(VNS-GA),以非冷链商品配送为研究对象,构造起求解物流配送车辆路径规划的数学模型。首先,以配送成本和缺货惩罚成本的最小化作为实现目标,构建了包括车辆使用成本、配送运输成本和时间窗口惩罚成本的配送路径优化模型;其次,运用变邻域遗传优化算法来实现多目标物流配送路径的优化;最后,以京东某北京配送中心的物流配送为例,运用MATLAB软件对VNS-GA算法模型的科学性及有效性进行仿真验证。经实证,VNS-GA算法与传统算法相比具有更好的全局和局部搜索能力。研究期望为配送车辆调度与配送路径规划提供更优的路径选择模型,从而降低物流配送成本和减少便利店因缺货造成的损失。

基于人工免疫-改进粒子群优化算法的机械臂轨迹规划研究

焊接机器人运动轨迹复杂、控制精度要求高。提出了一种满足多目标约束的轨迹规划方法。针对机器人轨迹平滑性要求,以5次非均匀有理B样条(Non-Uniform Rational B-Splines,NURBS)曲线为基础,对笛卡儿空间路径点进行参数化表达;根据工业机器人路径约束及工况需求,选取时间、能耗、跃度3个运动学指标作为目标优化函数,采用人工免疫双态粒子群进行轨迹优化;为了平衡粒子“探索”与“利用”,增加双模态模型,引入人工免疫系统,提升了粒子多样性与后期收敛能力;根据Pareto解集得到满足约束的焊接机器人各关节最优轨迹,通过Matlab仿真证明了方法的有效性;最后,针对空间相贯曲线焊缝进行了焊接试验。结果显示,规划的轨迹符合实际工程需求。

Multi-Path Routing and Resource Allocation in Active Network

An algorithm of traffic distribution called active multi-path routing (AMR)in active network is proposed. AMR adopts multi-path routing and applies nonlinear optimizeapproximate method to distribute network traffic among multiple paths. It is combined to bandwidthresource allocation and the congestion restraint mechanism to avoid congestion happening and worsen.So network performance can be improved greatly. The frame of AMR includes adaptive trafficallocation model, the conception of supply bandwidth and its' allocation model, the principle ofcongestion restraint and its' model, and the implement of AMR based on multi-agents system in activenetwork. Through simulations, AMR has distinct effects on network performance. The results show AMRisa valid traffic regulation algorithm.

MTSS: multi-path traffic scheduling mechanism based on SDN

Large-scale and diverse businesses based on the cloud computing platform bring the heavy network traffic to cloud data centers.However,the unbalanced workload of cloud data center network easily leads to the network congestion,the low resource utilization rate,the long delay,the low reliability,and the low throughput.In order to improve the utilization efficiency and the quality of services(QoS)of cloud system,especially to solve the problem of network congestion,we propose MTSS,a multi-path traffic scheduling mechanism based on software defined networking(SDN).MTSS utilizes the data flow scheduling flexibility of SDN and the multi-path feature of the fat-tree structure to improve the traffic balance of the cloud data center network.A heuristic traffic balancing algorithm is presented for MTSS,which periodically monitors the network link and dynamically adjusts the traffic on the heavy link to achieve programmable data forwarding and load balancing.The experimental results show that MTSS outperforms equal-cost multi-path protocol(ECMP),by effectively reducing the packet loss rate and delay.In addition,MTSS improves the utilization efficiency,the reliability and the throughput rate of the cloud data center network.

Rotary unmanned aerial vehicles path planning in rough terrain based on multi-objective particle swarm optimization

This paper presents a path planning approach for rotary unmanned aerial vehicles(R-UAVs)in a known static rough terrain environment.This approach aims to find collision-free and feasible paths with minimum altitude,length and angle variable rate.First,a three-dimensional(3D)modeling method is proposed to reduce the computation burden of the dynamic models of R-UAVs.Considering the length,height and tuning angle of a path,the path planning of R-UAVs is described as a tri-objective optimization problem.Then,an improved multi-objective particle swarm optimization algorithm is developed.To render the algorithm more effective in dealing with this problem,a vibration function is introduced into the collided solutions to improve the algorithm efficiency.Meanwhile,the selection of the global best position is taken into account by the reference point method.Finally,the experimental environment is built with the help of the Google map and the 3D terrain generator World Machine.Experimental results under two different rough terrains from Guilin and Lanzhou of China demonstrate the capabilities of the proposed algorithm in finding Pareto optimal paths.

基于Bi-RRT和TEB算法的风电水域多目标点路径规划

针对运维船舶需要依次抵达多个待运维机组处开展风机维护工作,提出一种在风电水域进行多目标点自主路径规划的方法。采用改进Bi-RRT算法进行全局路径规划,TEB算法用于局部路径规划,融合两种算法完成多目标点自主路径规划。引入基于均匀概率的分配机制对Bi-RRT进行改进以减少冗余搜索空间;采用对立扩展树新节点导向策略以增强采样过程中的导向性;通过路径平滑处理,进一步优化路径。利用改进后算法进行仿真实验,与改进前算法进行对比得到:改进后算法迭代次数减少50.4%,求解时间减少11.7%,路径长度缩短30.5%。另外,在ROS仿真平台中搭建合理的仿真环境,结果表明,在同样的地图环境中,改进的Bi-RRT与TEB融合算法较A*算法得到路径更为优越可靠,同时,设定多任务点验证了所提算法进行多目标点路径规划的有效性和可行性。

MRBCH: A Multi-Path Routing Protocol Based on Credible Cluster Heads for Wireless Sensor Networks

Wireless sensor networks are widely used for its flexibility, but they also suffer from problems like limited capacity, large node number and vulnerability to security threats. In this paper, we propose a multi-path routing protocol based on the credible cluster heads. The protocol chooses nodes with more energy remained as cluster heads at the cluster head choosing phase, and then authenticates them by the neighbor cluster heads. Using trust mechanisms it creates the credit value, and based on the credit value the multi-path cluster head routing can finally be found. The credit value is created and exchanged among the cluster heads only. Theoretical analysis combined with simulation results demonstrate that this protocol can save the resource, prolong the lifetime, and ensure the security and performance of the network.

Intelligent learning technique based-on fuzzy logic for multi-robot path planning

Soccer robot system is a tremendously challenging intelligent system developed to mimic human soccer competition based on the multi discipline research: robotics, intelligent control, computer vision, etc. robot path planning strategy is a very important subject concerning to the performance and intelligence degree of the multi robot system. Therefore, this paper studies the path planning strategy of soccer system by using fuzzy logic. After setting up two fuzziers and two sorts of fuzzy rules for soccer system, fuzzy logic is applied to workspace partition and path revision. The experiment results show that this technique can well enhance the performance and intelligence degree of the system.

Short Baseline Positioning with an Improved Time Reversal Technique in a Multi-path Channel

在水下面的一条多路径隧道的存在极大地减少放系统的短基线的精确性。在这份报纸，到放系统的短基线的一面时间颠倒镜子的申请被调查。时间颠倒镜子技术允许声学的信号更好集中在未知环境，它有效地减少了多路径的扩大声学的信号象一样改进了集中的信号。时间颠倒操作员的 signal-to-noise 比率(SNR ) 极大地增加了并且能被 ensonifying 获得水。这种技术被环境并且因此少些影响对复杂的浅水环境更适用。数字模拟和水池实验被用来表明这种技术的效率。

A new method to estimate DOA in CDMA system in multi-path environment

An algorithm for direction angle of arrival(DOA) estimation and array calibration of signals from multiple mobile users in the CDMA systems and multi-path environment was presented . The main idea is that the algorithm employs code-matched filter and model of the inter-symbol interference and multiple-access interference exactly. The correlation matrices of the received signals before and after code-matched filtering were employed to eliminate the effect of the additive white Gaussian noise, and a new mathematical problem was created, a new maximum likelihood method based on the strong law of large number was derived for DOA estimation and array calibration. Computer simulation results prove that the algorithm is effective.

Thermo-Calc based multi-component micro-segregation model and solidification paths calculations

On the basis of a multi-length scale modeling, a mixture-averaged multi-component /multiphase micro-segregation model was proposed without pre-set function for the micro-scale solute profile. The model explains the effect of morphologies of solidifying phases and solid back diffusion (SBD) on segregation, and covers the two limiting solidification cases of Scheil and Lever-rule models. A commercial Thermo-Calc software package/database was linked to the algorithms via its TQ6-interface for instantaneous determination of the related thermodynamic data of the multi-component alloys. The influences of cooling rate and other parameters on the solidification path and micro-segregation behavior were numerically investigated by sample calculation of the ternary Al-Cu-Mg alloys. A parallel experimental investigation on Al-Cu-Si alloys solidified under different cooling conditions was conducted to validate the theoretical model. Reasonable agreements were gained between the predicted solidification paths and the measured results.

SC-FDMA系统的MMSE-FSE算法分析

单载波频分多址(Single-Carrier Frequency Division Multiple Access,SC-FDMA)系统均衡器的输入信号通常是按符号间隔进行采样的,其对抽样时间十分敏感。在短波波段,由于多径反射显著,当多径延时接近符号周期长度时,对抽样时间敏感的缺点会被放大。针对短波信道的特征,研究了SC-FDMA系统的分数间隔均衡器(Fractional Spaced Equalizer,FSE)模型,通过与符号间隔均衡器对比发现,虽然符号间隔均衡器可以补偿接收信号的频率响应,但其对短时延衰落信道的补偿效果较差;FSE对于抽样时间的选择不敏感,在多径信道下能够获得更好的性能。链路仿真结果表明,在短时衰落信道环境下,FSE的译码性能比符号间隔均衡器有最大1.5 dB的增益。

Multi-Behavior Fusion Based Potential Field Method for Path Planning of Unmanned Surface Vessel

The problem of the unmanned surface vessel (USV) path planning in static and dynamic obstacle environments is addressed in this paper. Multi-behavior fusion based potential field method is proposed, which contains three behaviors: goal-seeking, boundary-memory following and dynamic-obstacle avoidance. Then, different activation conditions are designed to determine the current behavior. Meanwhile, information on the positions, velocities and the equation of motion for obstacles are detected and calculated by sensor data. Besides, memory information is introduced into the boundary following behavior to enhance cognition capability for the obstacles, and avoid local minima problem caused by the potential field method. Finally, the results of theoretical analysis and simulation show that the collision-free path can be generated for USV within different obstacle environments, and further validated the performance and effectiveness of the presented strategy.

Novel multi-path routing scheme for UWB Ad hoc network

The routing protocols play an important role for ad hoc networks performance.As some problems with DSR,SMR,and AMR protocols were analyzed,a new routing protocol suitable for UWB Ad hoc networks was proposed in this paper.The new routing protocol utilize an act of orientation of UWB and tries to get sufficient route information and decrease the network load caused by route discovery at the same time.Simulation results show that the routing load of the new protocol is lower and throughput is higher than that of DSR.While the node’s mobility increases,these advantages become more obvious.

基于改善率统计的MAPF-LNS2+算法

MAPF-LNS2是一种基于大邻域搜索的算法,用于解决多智能体路径规划问题。优势在于其速度更快,在大多数情况下提供接近最优解的解决方案。但该算法在分配权重时仅考虑当前邻域搜索策略的近期表现并有可能分配了较高的权重,使其他邻域搜索策略出现短暂的“饥饿”现象,导致增加算法的总运行时间。针对该问题基于MAPF-LNS2算法,通过引入改善率统计和时间窗口提出了一种新的多智能体路径规划算法。结果表明,无论是在运行时长还是成功率方面,MAPF-LNS2+算法均优于MAPF-LNS2算法,运行时间最高降低了65.1%,成功率最大提升了16%。

Adaptive genetic algorithm for path planning of loosely coordinated multi-robot manipulators

Adaptive genetic algorithm A SA GA, a novel algorithm, which can dynamically modify the parameters of Genetic Algorithms in terms of simulated annealing mechanism, is proposed for path planning of loosely coordinated multi robot manipulators. Over the task space of a multi robot, a strategy of decoupled planning is also applied to the evolutionary process, which enables a multi robot to avoid falling into deadlock and calculating of composite C space. Finally, two representative tests are given to validate A SA GA and the strategy of decoupled planning.

Link-Vertex Topology Aggregation for Multi-domain Path Computation with Hierarchical PCE Architecture

Inter-domain path computing is one big issue in multi-domain networks. The Hierarchical Path Computing Element (H-PCE) is a semi-central architecture for computing inter-domain path. To facilitate H-PCE in inter-domain path computing, this paper proposed a topology aggregation scheme to abstract the edge nodes and their connected inter-domain link as one vertex to achieve more optimal paths and confidentiality guarantee. The effectiveness of the scheme has been demonstrated on solving wavelength routing in multi-domain Wavelength Division Multiplexing (WDM) network via simulation. Simulation results show that this scheme reduces at least 10% inter-domain blocking probability, compared with the traditional Domain-to-the-Node (DtN) scheme.

面向多行程取送货车辆路径问题的混合NSGA-Ⅱ

针对多行程取送货车辆路径问题(VRP)收敛性与多样性相互制约的问题,提出一种融合自适应大邻域搜索(ALNS)算法和自适应邻域选择(ANS)的混合快速非支配排序遗传算法(NSGA-Ⅱ-ALNS-ANS)。首先,考虑初始解对算法收敛速度的影响,提出一种改进的后悔插入法以获得高质量初始解;其次,结合取送货问题特性,设计多组破坏和修复算子,以及多种邻域结构,提高算法的全局搜索能力和局部搜索能力;最后,设计基于随机采样的最佳拟合下降(BFD)算法与高效的可行解评价标准,生成路径分配方案。采用不同规模的标准公开算例进行仿真实验,与模因算法(MA)相比,所提算法的最优解质量提升了27%。实验结果表明,所提算法可快速得到满足多重约束的高质量车辆多行程路径分配方案,并在收敛性与多样性上优于对比算法。

多尺度特征融合的RGB-D图像显著性目标检测

显著性目标检测是计算机视觉的一个基础问题,目前很多基于深度学习的显著性检测方法都是将RGB图像和深度图按照输入融合或结果融合的方法进行特征融合,但这些方法并不能有效地融合特征图,为了提升显著性目标检测算法性能,提出了一种多尺度特征融合的RGB-D图像显著性目标检测方法。将模型主体设计为两个特征编码器、两个特征解码器和一个跨模特多尺度特征交错融合模块。两个特征编码器分别对应RGB图和深度图,其采用经过ImageNet数据集预训练的ResNet50网络,特征解码器用于解码编码器的五种不同尺度的输出,跨模态多尺度特征交错融合模块用于融合解码器和编码器提取的不同尺度的特征图,并将五个层次的融合结果进行拼接和降维,输出最终的显著性预测图。实验在四个公开的显著性数据集上与以往具有代表性的十个模型进行了比较,该模型在各个数据集上,相比于性能第二的模型,S-measure平均提高了0.391%,MAE平均减少了0.330%,F-measure平均减少了0.405%。提出了一种多尺度特征融合模型,摒弃了以往融合的方式,采用特征融合,将浅层和深层的特征分别进行交错融合,实验表明,提出的方法较以往的方法有更强的性能,能够取得更好的效果。