适用于自由曲面高速高精加工的旋转轴位置优化算法

针对自由曲面加工中机床旋转轴角度变化过大导致刀具姿态误差较大和旋转轴频繁加减速问题,在分析刀具姿态误差与旋转轴转动幅度间关系的基础上,提出一种适用于自由曲面高速高精加工的旋转轴位置优化算法。在根据旋转轴转动幅度条件确定初始修正区域后,采用递归扩充原则确定待修正区域,并在保证工件坐标系下刀具切触点坐标不变的情况下,采用等幅旋转法则对各待修正区域的旋转轴坐标值进行优化。仿真和实际加工结果表明,本算法能够对加工中旋转轴角度进行修正,避免大幅旋转轴转动,减少加工中的刀具姿态误差,在提高加工精度的同时缩短了加工时间。     

基于遗传算法的三坐标测量机测量路径规划方法

针对现有三坐标测量机检测路径规划方法的不足,提出和构建了零件检测特征群数学模型和求解流程,在此基础上,根据检测工作平面、检测测头及检测测针变动次数和检测路径构建优化目标函数,从宏观和微观两个层面分别应用矩阵交叉遗传算法和序列规划遗传算法进行零件检测特征路径的优化求解。最后以Hexagon公司检测零件为例,说明了零件初始检测信息的获取以及算法的优化求解过程。实践证明,该方法快速有效,且具有良好的工程应用价值。     

基于父子混合选择遗传算法的大型压力机主梁的最优设计

主梁是大型压力机的关键受力构件之一,其最优设计问题是一类很难求解的非线性规划问题.传统的优化方法在解决这类复杂优化问题时显示出自身的一些不足.针对传统优化算法的局限性,提出用简单实用的基于父子混合选择遗传算法,对大型压力机的主梁进行优化设计.并用一个仿真算例验证了该算法的有效性和可行性.     

Integrated scheduling of flexible manufacturing system using evolutionary algorithms

Effective sequencing and scheduling of the material handling system (MHS) have an impact on the productivity of the flexible manufacturing system (FMS). The MHS cannot be neglected while scheduling the production tasks. It is necessary to take into account the interaction between machines and MHS. This paper highlights the importance of integration between production schedule and MHS schedule in FMS. The Giffler and Thompson algorithm with different priority dispatching rules is developed to minimize the makespan in the FMS production schedule. Its output is used for MHS scheduling where the distance traveled and the number of backtrackings of the automated-guided vehicles are minimized using an evolutionary algorithms such as an ant colony optimization algorithm and particle swarm optimization (PSO) algorithm. The proposed evolutionary algorithms are validated with benchmark problems. The results available for the existing algorithms are compared with results obtained by the proposed evolutionary algorithms. The analysis reveals that PSO algorithm provides better solution with reasonable computational time.     

Navigation planning for mobile robotic devices in modular warehouses

This paper deals with the problem of navigation and planning of an automated warehouse equipped with mobile robotic devices. A generalised layout of the warehouse is considered here, which is a modular construction type. The path planning algorithm (optimises the path for the shortest distance to the goal) and the collision avoidance strategy for a multiple robot environment are developed based on velocity and distance bounds. The landmarks are assumed to supply all pertiment information regarding the module identification and the movement directions, while the sensors are assumed to be capable of maintaining the robot in its correct track and understand the knowledge contained in the landmarks. The path planning and collision avoidance algorithms are programmed and simulated for a multiple robot environment in a construction site warehouse.     

遗传算法在机械优化设计中的应用

遗传算法是一种自适应启发式全局搜索算法,具有传统算法不可比拟的优点,更易于求解各种优化问题。在不断改进、不断成熟的过程中,遗传算法得到了广泛的应用,其中在机械优化设计领域得到了大量应用。通过遗传算法工具箱及针对基本遗传算法进行改进后的遗传算法两个方面,论述了遗传算法在机械优化设计中具有的优势,介绍了近年来在相关领域中成功应用的一些典型范例。并对遗传算法在机械优化设计中的发展及前景作了必要的讨论。     

A genetic algorithm and particle swarm optimization for no-wait flow shop problem with separable setup times and makespan criterion

This paper considers the problem of no-wait flow shop scheduling, in which a number of jobs are available for processing on a number of machines in a flow shop context with the added constraint that there should be no waiting time between consecutive operations of a job. Each operation has a separable setup time, meaning that the setup time of an operation is independent on the previous operations; and the machine can be prepared for a specific operation and remain idle before the operation actually starts. The considered objective function in this paper is the makespan. The problem is proven to be NP-hard. In this paper, two frameworks based on genetic algorithm and particle swarm optimization are developed to deal with the problem. For the case of no-wait flow shop problem without setup times, the developed algorithms are applied to a large number of benchmark problems from the literature. Computational results confirm that the proposed algorithms outperform other methods by improving many of the best-known solutions for the test problems. For the problems with setup time, the algorithms are compared against the famous 2-Opt algorithm. Such comparison reveals the efficiency of the proposed method in solving the problem when separable setup times are considered.     

基于改进微粒群算法的起重机主梁优化设计

现阶段起重机金属结构的优化设计一般都采用传统的优化算法,但传统算法普遍存在或对目标函数有解析性要求、或易陷入局部最优、或耗时较长的问题.微粒群优化算法是一种基于群体智能的新型优化算法,它可调参数少、对解析性无要求,已成功应用于多种领域.将微粒群算法应用于起重机主梁的优化中,经实例验证,在保证优化性能的前提下,基于微粒群算法的设计方法与网格算法相比,优化速度显著提升.     

A~*算法在移动机器人路径规划中的应用

采用A*算法对已知环境中的移动机器人路径规划问题进行研究。利用栅格法建立环境模型,然后对节点的选择进行分析,最后通过MATLAB仿真。仿真结果表明算法能找到一条从起点到终点的较优路径,验证了算法的有效性。     

RFID标签双模式阻塞防碰撞算法

为解决“驻留标签之间碰撞、驻留标签与迁入标签之间碰撞、当驻留率较低时传统阻塞算法产生大量空闲时隙”等问题，提出了一种双模式的阻塞防碰撞算法。首先开展了对自适应二叉树分割算法（ABS）和传统阻塞算法的研究和性能分析。然后在保留上述算法优势的基础上，结合对迁入标签数目的估计算法，解决前面所提到的问题，并从标签数目、驻留率和迁入率等方面进行了算法的性能比较。理论分析和仿真实验都证明了该算法的有效性和可靠性。     

基于改进A*算法的AGV路径研究

路径规划能力是AGV(Automated Guided Vehicle,自动导引运输车)系统智能化程度的体现。在众多算法中,A~*算法使用代价消耗估算方式达到较快的计算能力,被广泛应用于AGV的路径规划中,但仍存在局部最优的规划问题,规划的路径上存在冗余节点和较多不必要拐点。为减少运输路径中的总能耗,缩短路径总长度和减少AGV转弯次数,采用分裂和筛选的方案对传统A~*算法进一步优化,提出改进A~*算法,使其在实际工作环境中搜索更加迅速、考虑更加周密。在传统A~*算法基础上,在未知节点的启发函数里增加转弯权值,可以在计算规划过程中考虑转向所带来的消耗,从而减少转弯次数。使用任务分裂方案可以尽可能多地选择出较优路径,其中的最优解能够实现得转弯较少,展现出比较平滑的线路。基于Ubuntu下ROS系统版本进行仿真,对比实验结果表明,改进A~*算法在规划时间、总行程以及转弯消耗等方面都优于传统A~*算法,提升了AGV的实际运行效率,减少了AGV小车的耗能,可以缩短路径搜索规划时间,更符合工厂环境对AGV的需求。     

基于拥挤距离排序的多目标粒子群优化算法及其应用

针对多目标粒子群算法在全局寻优能力和Pareto集多样性上的不足,提出基于拥挤距离排序的多目标粒子群算法.该算法采用精英策略,基于个体拥挤距离降序排列,进行外部种群的缩减和全局最优值的更新,并在内部粒子群中引入小概率变异机制,增强算法的全局寻优能力,控制Pareto最优解的数目,同时保证其收敛性和多样性特征.在电梯曳引性能的多目标优化应用中,证明了该算法对于两目标和三目标优化问题求解的有效性.不同规模实例的运算对比表明,该算法在Pareto前沿的收敛性和多样性方面均优于改进强度Pareto进化算法,且缩短了运算时间,具有较高的效率与鲁棒性.     

用于通用ATE开关资源测试路径优化的算法

文章在分析和比较目前常用的几种路径优化算法的基础上,尝试将蚂蚁算法用于通用ATE开关资源测试中测试路径的优化。通过将蚂蚁算法信息素的引入,使得蚂蚁算法能够以较稳定的速度逼近最优解,而且收敛速度较快,从而说明将蚂蚁算法用于解决测试路径优化问题的有效性。     

大尺寸动态视觉测量系统的并行加速

由于现有以大数据量和计算量为基础的大尺寸动态视觉测量系统处理速度较慢,本文建立了一个高速大尺寸动态视觉测量系统,并对该系统涉及的特征点中心定位、编码点识别、相机定向等算法进行了并行化研究。首先,分析了在不同测量条件下各个主要算法的时间消耗情况及每个主要算法的并行性;然后,对常规的特征点中心定位和编码点识别算法做了介绍,分别提出了特征点中心并行快速定位和编码点并行快速识别算法,并详细说明了这两种并行快速算法的实现原理。最后,针对大量原子操作的问题,提出了线程束集体原子操作的优化方法。实验结果表明:在不损失定位精度和识别率的前提下,图像中包含300个点时的并行方案比串行方案的时间开销减少了42%,当点数达到20 000时,时间开销减少91%以上。实验显示提出的并行设计方案有效地提高了处理速度,解决了大尺寸动态视觉测量系统实时性差的问题。     

Incomplete mesh-based tool path generation for optimum zigzag milling

The majority of mechanical parts are manufactured by milling machines. Hence, geometrically efficient algorithms for tool path generation and physical considerations for better machining productivity with guarantee of machining safety are the most important issues in milling tasks. In this paper, we present an optimized path-generation algorithm for zigzag milling, which is commonly used in the roughing stage as well as in the finishing stage, based on an incomplete two-manifold mesh model, namely, an inexact polyhedron that is widely used in recent commercialized CAM software systems. First of all, a geometrically efficient tool path generation algorithm using an intersection points-graph is introduced. Although the tool path obtained from geometric information has been successful to make a desirable shape, it seldom considers physical process concerns like cutting forces and chatter. In order to cope with these problems, an optimized tool path that maintains constant MRR in order to achieve constant cutting forces and to avoid chatter vibrations at all times is introduced and the result is verified. Additional tool path segments are appended to the basic tool path by using a pixel-based simulation technique. The algorithm was implemented for two-dimensional contiguous end-milling operations with flat end mills and cutting tests were conducted by measuring the spindle current, (which reflect machining situations) to verify the significance of the proposed method.     

基于遗传算法的可控螺旋角锥齿轮传动的优化设计

传统仿形法加工锥齿轮齿形误差大导致载荷不均、寿命短,而可控螺旋角锥齿轮是一种基于数控加工技术的新型雏齿轮,其为使用普通机床实现大型锥齿轮的精加工开辟了一条新途径.但该齿轮体积大是其缺点,本文通过对该齿轮传动的分析与设计,建立了优化数学模型,以体积最小作为优化目标,利用遗传算法进行优化,与传统优化方法进行了比较,结果表明,遗传算法用于求解可控螺旋角锥齿轮传动多变量、多约束优化问题的有效性和正确性,具有实际应用价值.     

轮毂曲面机器人力控磨抛路径规划方法

针对复杂轮毂曲面的机器人力控磨抛问题,根据预设的平行扫掠线模式进行曲面分割。在各子曲面,根据接触力及材料去除数值模型,构建以磨抛总量最大及残余磨抛量最小为目标的约束非线性优化问题,进而规划各路径离散点的驻留时间及相邻平行路径间距。通过解决非线性整数规划问题,对磨抛工具在子曲面间的抬降进行规划。实验结果表明,该算法能够规划出全覆盖磨抛路径,磨抛量达到预期,残余磨抛量较为平均,磨抛效率较高。     

Application of hierarchical facility location problem for optimization of a drone delivery system: a case study of Amazon prime air in the city of San Francisco

In the last decade, aerial delivery system has been considered as a promising response to increasing traffic jams and incremental demand for transportation. In this study, a distance-constrained mobile hierarchical facility location problem is used in order to find the optimal number and locations of launch and recharge stations with the objective of minimizing the total costs of the system. System costs include establishment cost for launching and recharge stations, drone procurement, and drone usage costs. It is supposed that the demand occurs according to Poisson distribution, distributed uniformly along the network edges and is satisfied by the closest open facility. Since the flying duration of a drone is limited to its endurance, it may visit one or more recharge stations to reach to the demand point. This route is calculated by the shortest path algorithm, and the Euclidean distance is considered between nodes and facilities. It is proved that facility location problems are NP-hard on a general graph. Accordingly, heuristic algorithms are proposed as solution method. To illustrate the applicability of the algorithms, a case study is presented and the results are discussed.     

Physical topology optimization of infrastructure health monitoring sensor network for high-speed rail

With the rapid development of high-speed rail (HSR) systems, the security and safety of these huge systems are becoming the primary concerns for passengers. HSR infrastructure plays an important role in HSR systems, making the maintenance of security and safety of the HSR infrastructure especially important. Meanwhile, sensor network technologies allow the realization of real-time and all-weather monitoring of HSR infrastructure. This paper analyzes the application requirements and characteristics of infrastructure health monitoring sensor network (IHMSN) through construction of a three-layer IHMSN which is composed of end devices, repeater points, and access points. The physical topology optimization goal of IHMSN is to set the optimal number of network nodes (namely, minimum cost) as well as the best physical connections. Given types and amount of the end devices, a multiple knapsack model is established which converts the physical topology optimization problems into multiple knapsack problems. Based on the different needs of practical application, three different cases (basis case, adding devices case and weight-based case) are proposed, and the corresponding models are built. Some artificial intelligence algorithms and a traditional dynamic programming algorithm are presented to solve the problems. In addition, a general algorithmic finite state machine is proposed to describe the solving process. After comparing these algorithms in execution time, memory, and optimal results, the genetic algorithm and particle swarm optimization algorithm stand out when used to solve the basic case as well as the extended cases. The numerical results show that these proposed models and algorithms can effectively solve the physical topology optimization problem of IHMSN for HSR systems. Moreover, these methods can effectively reduce network costs and provide a theoretical basis for network communication link optimization.     

面向复杂曲面的喷涂机器人喷枪路径的规划

根据试验数据给出了涂层生长速率模型,将自由曲面通过拓扑关系生成若干个平面片,在每一片上进行喷枪速率及轨迹间距的优化,基于面片交界处喷枪轨迹为PA-PA时涂层厚度均匀性较好的原则,根据面片的边界几何特征对喷枪路径进行了规划,提出了用变偏距的方法优化Z型路径模式,该方法通过选择两轨迹间的偏距极值及始末轨迹的长度来确定每相邻轨迹间的偏角来达到变偏距的目的,给出了其中参数的计算方法和优化算法。最后通过实例验证了该算法对Z型路径模式的优化具有一定的可行性。