RESEARCH ON COMBINATION AND PLANNING OF PROCESSING UNITS UNDER CIMS CONDITION

A method of the rational combinging and planning of the given processing machines into units under the condition of computer integrated manufacturing systems is presented. Here the modelling method is a kind of queuing network model with the change of productivity, which has been checked in the reality and effectivencss by a manufacturing case in China

A multiple heterogeneous UAVs reconnaissance mission planning and re-planning algorithm

Reconnaissance mission planning of multiple unmanned aerial vehicles(UAVs)under an adversarial environment is a discrete combinatorial optimization problem which is proved to be a non-deterministic polynomial(NP)-complete problem.The purpose of this study is to research intelligent multiUAVs reconnaissance mission planning and online re-planning algorithm under various constraints in mission areas.For numerous targets scattered in the wide area,a reconnaissance mission planning and re-planning system is established,which includes five modules,including intelligence analysis,sub-mission area division,mission sequence planning,path smoothing,and online re-planning.The intelligence analysis module depicts the attribute of targets and the heterogeneous characteristic of UAVs and computes the number of sub-mission areas on consideration of voyage distance constraints.In the sub-mission area division module,an improved K-means clustering algorithm is designed to divide the reconnaissance mission area into several sub-mission areas,and each sub-mission is detected by the UAV loaded with various detective sensors.To control reconnaissance cost,the sampling and iteration algorithms are proposed in the mission sequence planning module,which are utilized to solve the optimal or approximately optimal reconnaissance sequence.In the path smoothing module,the Dubins curve is applied to smooth the flight path,which assure the availability of the planned path.Furthermore,an online re-planning algorithm is designed for the uncertain factor that the UAV is damaged.Finally,reconnaissance planning and re-planning experiment results show that the algorithm proposed in this paper are effective and the algorithms designed for sequence planning have a great advantage in solving efficiency and optimality.

Construction and Application of Combined Evaluation Model of Regional Water Quality Plan

[Objective] The aim was to study the construction and application of combined evaluation model of regional water quality plan. [Meth- od] By dint of layer analysis, subjective and objective model of entropy evaluation, the water quality plan in Jinghe was evaluated. Combined evalu- ation model based on information entropy were constructed, and considering the single model evaluation result, the optimal water quality plan was selected. [ Result] The combination weight result suggested that COD amount was the most essential indicator in water quality plan and embodied the importance of water environment protection, which met basic objective of environment protection and social, economic effects. Combined evalu- ation indicated that in the sixteen plans, plan 16 was of highest comprehensive evaluation value, and can be considered as optimum water quality plan. [ Conclusion] Combined evaluation model can effectively list the advantages of each evaluation model and improve the dependability of water quality plan, and provided a new research idea for the optimal evaluation of water pollution control plan.

An iterative approach to an integrated land use and transportation planning tool for small urban areas

There has been increasing interests in developing land use models for small urban areas for various planning applications such as air quality conformity analysis. The output of a land use model can serve as a major input to a transportation model; conversely, transportation model output can provide a critical input to a land use model. The connection between the two models can be achieved by an accessibility measure. This paper presents an iterative approach to solving a regression-based land use model and a transportation model with combined trip distribution- assignment. A case study using data from a small urban area is presented to illustrate the application of the proposed modeling framework. Tests show that the procedures can converge, and the modeling framework can be a valuable tool for planners and decision-makers in evaluating land use policies and transportation investment strategies.

Role of Metacognition in Mathematical Problem Solving Process of Permutations and Combinations--Basic Study for CAI Software Development

When solving a mathematical problem, we sometimes encounter a situation where we can not reach a correct answer in spite of acquiring knowledge and formula necessary for the solution. The reason can be attributed to the lack in metacognitive abilities. Metacognitive abilities consist of comparing the difficulty of problem with own ability, proper plan of solution process, and conscious monitoring and control of solution process. The role and importance of metacognitive ability in mathematical problem solving of permutations and combinations was explored. Participants were required to solve five practical problems related to permutations and combinations. For each problem, the solution process was divided into： （1） understanding （recognition） of mathematical problem; （2） plan of solution; （3） execution of solution. Participants were also required to rate the anticipation whether they could solve it or not, and to rate the confidence of their own answer. According to the total score of five problems, the participants were categorized into the group of the high test score and the group of the low test score. As a result, at the plan and the execution processes, statistically significant differences were detected between the high and the low score groups. As for the rating on the anticipation of result and the confidence of own answer, no significant differences were found between both groups. Moreover, the relationship between the score of plan process and the score of execution process was statistically correlated. In other words, the more proper the plan process was conducted, the more proper solution the participants reached. In such a way, the importance of metacognitive ability in the solving process, especially the plan ability, was suggested.

Application of Interval Algorithm in Rural Power Network Planning

Rural power network planning is a complicated nonlinear optimized combination problem which based on load forecasting results, and its actual load is affected by many uncertain factors, which influenced optimization results of rural power network planning. To solve the problems, the interval algorithm was used to modify the initial search method of uncertainty load mathematics model in rural network planning. Meanwhile, the genetic/tabu search combination algorithm was adopted to optimize the initialized network. The sample analysis results showed that compared with the certainty planning, the improved method was suitable for urban medium-voltage distribution network planning with consideration of uncertainty load and the planning results conformed to the reality.

INTEGRATED APPROACH TO ASSEMBLY SEQUENCE PLANNING OF C0MPLEX PRODUCTS

Assembly sequence planning will be more difficult due to the increasingcomplexity of products. An integrated approach to assembly sequence planning of complex productsapplying de-composition-planning-combination strategy is presented. First, an assembly is decomposedinto a hierarchical structure using an assembly structure representation based on connectors. Then,an assembly planning system is used to generate the sequences that are locally optimal for eachleaf partition hi the structure hierarchy. By combining the local sequences systematically in abottom-up manner and choosing suitable ones from the merged sequences, the assembly sequence of eachparent structure including the whole assembly is generated. An integrated system has beencompleted. A complex product is given to illustrate the feasibility and the practicality of theapproach.

煤矿井下掘进机器人路径规划方法研究

针对煤矿非全断面巷道条件下掘进机器人移机难度大、效率低下等问题,分析了煤矿井下非结构化环境特征及掘进机器人运动特性,提出了基于深度强化学习的掘进机器人机身路径规划方法。利用深度相机将巷道环境实时重建,在虚拟环境中建立掘进机器人与巷道环境的碰撞检测模型,并使用层次包围盒法进行虚拟环境碰撞检测,形成巷道边界受限下的避障策略。考虑到掘进机器人形体大小且路径规划过程目标单一,在传统SAC算法的基础上引入后见经验回放技术,提出HER-SAC算法,该算法通过环境初始目标得到的轨迹扩展目标子集,以增加训练样本、提高训练速度。在此基础上,基于奖惩机制建立智能体,根据掘进机器人运动特性定义其状态空间与动作空间,在同一场景下分别使用3种算法对智能体进行训练,综合平均奖励值、最高奖励值、达到最高奖励值的步数以及鲁棒性4项性能指标进行对比分析。为进一步验证所提方法的可靠性,采用虚实结合的方式,通过调整目标位置设置2种实验场景进行掘进机器人的路径规划,并将传统SAC算法和HER-SAC算法的路径结果进行对比。结果表明:相较于PPO算法和SAC算法,HER-SAC算法收敛速度更快、综合性能达到最优;在2种实验场景下,HER-SAC算法相比传统SAC算法规划出的路径更加平滑、路径长度更短、路径终点与目标位置的误差在3.53 cm以内,能够有效地完成移机路径规划任务。该方法为煤矿掘进机器人的自主移机控制奠定了理论基础,为煤矿掘进设备自动化提供了新方法。

路径交叉测绘任务规划问题

不同于传统多旅行商问题,小型飞机测绘任务规划问题的每个测绘目标需要测绘多个测绘载荷,同时多次测绘间要有时间间隔,称之为路径交叉的多旅行商路径规划问题。针对点目标测绘任务场景,将最少飞机数量的求解目标转化为求解最短航行路径。在采用遗传算法求解最短路径的基础上,结合探测载荷约束、探测任务时长约束等条件,进一步规划出最优的调度方案。针对点目标和区域目标测绘任务规划问题,考虑各机场测绘任务工作量的均衡,定义测绘工作量指标为每个机场完成的测绘目标点和目标道路的数目,求解调度策略和飞机数量。在此基础上求解均衡性,使3个机场探测的目标点和目标道路数量相当。结果表明,所提方案兼顾了测绘代价与任务分配的均衡性。

生鲜农产品车辆和无人机组合配送路径优化及效果测试

【目的】为提升生鲜农产品的配送效率,提出生鲜农产品车辆与无人机组合配送路径优化方案。【方法】按照生鲜农产品冷链配送体系要求,采用模糊K-means聚类方法确定生鲜农产品配送中心;定义配送中心位置为车辆和无人机组合配送的起点,以生鲜农产品配送总成本最小为目标函数,利用蚁群算法和无人机物流车协调配送算法求解上述构建的目标函数,获取最低配送总成本的配送路径规划结果;引入安全启发函数优化蚂蚁转移规则,获取安全最高的无人机最优配送路径。再按照该方法,将生鲜农产品按照质量划分为重件和轻件,并计算重件和轻件在配送过程中产生的成本,获取在不同的总配送生鲜农产品快件数量下,优化前与优化后的配送成本。【结果】效果测试表明,该方法具有良好的聚类效果,簇类凝聚度(Davies-Bouldin, DB)指数值均低于0.15,可合理选取配送中心,保证配送中心的覆盖程度。并且通过对比该方法应用前后的数据对比可知,应用前重件和轻件的配送成本明显更高于应用后的成本。【结论】该方法可以更高质量地完成车辆和无人机组合配送路径规划,能够显著降低生鲜农产品的配送总体成本,应用效果满足应用需求,提升配送效率。

面向多传感系统协同测量场的站位规划方法

针对大型构件多传感系统协同测量中各系统测量可达性模型多样化、多系统测量精度不均衡而导致的组合式测量站位设置多依赖测量人员经验以及需要不断尝试获取合适站位的问题,提出一种多传感系统协同测量场的站位规划方法。首先,考虑工装遮挡问题,对协同测量场中的组合式测量可达性模型进行优化,建立基于?鱼优化算法的有工装站位初值求解模型,解算组合式测量系统各测量站位初始值;其次,建立协同测量精度模型,以测量精度最佳为约束条件,建立观测值的加权均方根误差和矢量角度测量误差的优化目标函数,基于牛顿迭代算法不断迭代和更新到最佳精度站位坐标;最后,以某目标模拟器满足位置、姿态初始装调精度需求为例,进行组合式协同测量站位规划实验,优化后测量数据均方根误差为0.032 mm,相较于优化前测量规划位置测量精度提高34%,角度测量精度提高9.5%。该方法可有效地提高测量精度及可视化效果,为大型构件测量领域的进一步研究提供理论及应用参考。

基于组合权重TOPSIS的超限货物运输方案评价

超限货物运输方案是铁路安全运输超限货物的重要前提和保障。为实现超限货物运输方案的优选,提出一种基于组合权重和TOPSIS法的铁路超限货物运输方案评价模型。从装载加固方案、线路条件、运输组织复杂程度和运输费用4个方面分析超限货物运输方案的影响因素,确定方案评价指标,构建综合评价指标体系。运用博弈论原理计算方案评价指标的组合权重,其中主观权重由G1法确定,客观权重由熵权法确定。运用TOPSIS法对运输方案进行评价,构建基于组合权重和TOPSIS法的超限货物运输方案的综合评价模型。最后给出超限货物运输实例,运用所构建的评价模型对各运输方案进行评价。结果表明,建立的方案评价模型能够科学、合理地对超限货物运输方案进行比选。

十二杆张拉整体结构动态分析及路径规划研究

张拉整体因其区别于传统结构的特点在土木和可动结构领域有广泛的发展前景,目前学者对于多步态或更复杂的球形张拉整体研究较少,且一些传统路径规划方法不适用于多面体张拉整体结构.因此,本文采用几何方法找寻了一种多步态的十二杆球形张拉整体结构(Snub-12)的合理构型,并用找形方法进行了验证.定义并分析了Snub-12的多种基本步态和各步态形成的理论路径空间,并将其与单步态的6杆球形张拉整体结构(TR-6)进行对比,明确了两种结构运动的特点和区别.对快速搜索随机树算法进行改进并利用其产生引导路径,结合Snub-12步态组合的情况,生成适合不同场景的合理运动路径,最后通过仿真分析验证了方法的可行性和有效性.分析结果表明:同等条件下,不论是路径空间中盲区占比还是独立滚动步态的翻滚步长,Snub-12均优于TR-6,更适宜开展长距离运动.基于引导策略的路径规划方法可以解决多步态张拉整体结构的路径规划问题,这丰富了球形张拉整体结构的运动理论,可以为该类球形张拉整体可动结构的实际应用提供了理论支撑.

集群化发展模式下风电场预测、规划及控制关键技术综述

随着我国风电行业的快速发展,规模化发展风电对能源转型的推进至关重要。然而,由于风电场所处的复杂环境和高昂的建设运营成本等因素,集群化发展模式下的风电场面临着一系列技术难点和挑战。因此,文中针对集群化发展模式下风电场的建设和运营,重点总结了相关的预测、规划及控制关键技术。文中围绕风电场集群的关键技术与研究思路进行了归纳总结;针对风电场集群的特点,包括风资源量化表征与预测技术、多风电场协同优化规划技术以及多风电场控制与运行技术进行了详细探讨,对于每个技术领域,分析了当前的研究现状和取得的成果;最后,阐明了风电场集群建设和运营关键技术领域的发展趋势,并指出了待解决的技术难点,通过总结这些技术的研究成果为我国风电的规模化、集群化开发提供参考。

基于博弈论组合赋权和改进优劣解距离法的输变电工程建设时序规划

针对输变电工程建设时序有待优化的问题,对输变电工程建设优先级评价方法进行了研究。首先,从必要性、经济性、效率性、环保性4个维度出发,构建输变电工程建设优先级评价指标体系;然后,基于博弈论的思想将分别通过序关系分析法和指标相关性权重确定法求得的主客观权重进行结合,引入灰色关联分析法对基于组合赋权的优劣解距离法进行改进,构建输变电工程建设优先级评价模型;最后,对某省电网规划项目库中4个拟建220 kV输变电工程进行建设优先级评价并展开建设时序规划。结果表明:所提出的评价方法适用性较强,能够有效辅助电网基建规划。

基于势场增强烟花算法的二维全局路径规划

高质量路径是未来无人自主作战的重要前提,针对复杂障碍环境下路径规划问题,提出基于势场增强烟花算法(Potential-field Enhanced Fireworks Algorithm,PEFWA)的路径规划方法。建立规划空间模型与动态维数路径描述模型,设立包含可行性因素与长度因素的目标函数,将路径规划问题转化为最优化问题;设计动态维数烟花初始化与维度增删操作,使相邻维度个体满足距离约束;提出基于障碍空间信息的爆炸幅度计算方法和连续维度选择方法,生成改进爆炸火花,提高全局搜索能力;引入势场引导策略,生成势场增强爆炸火花,让所选维度在合力方向上多次搜索,提高局部优化能力;采用交叉组合策略生成变异火花,并对超出规划空间的维度个体进行删减操作,提高多样性烟花高效产生能力;提出基于余弦相似度的双层锦标赛选择策略,提高烟花特征延续能力。采用相同基准函数,将PEFWA与烟花算法(Fireworks Algorithm,FWA)、粒子群优化(Particle Swarm Optimization,PSO)算法、遗传算法(Genetic Algorithm,GA)进行对比。研究结果表明:PEFWA的优化性能更强;在相同复杂障碍环境下进行多次路径规划仿真实验,验证了PEFWA中各个模块的有效性,与PSO算法、GA、A*算法相比,PEFWA在规划成功率、路径长度、路径光滑度、结果鲁棒性等方面均有优势;PEFWA在二维全局路径规划问题上具有有效性与优越性。

基于深广结合算法的迷宫机器人路径规划技术研究

针对矿井中复杂环境下巡检机器人存在路径规划能力较差、任务执行效率偏低的问题,文中将深度和广度路径搜索方法相结合,提出了一种机器人路径规划算法。通过深广融合得到A*路径规划算法,并将其作为全局路径规划的方法。对于算法中存在规划路径过长且平滑度较差的不足,使用人工势能法对局部路径加以优化,以提高路径规划的准确度。同时还利用贝塞尔曲线进行路径平滑操作,进而增强了算法的工程应用能力。实验测试结果表明,该算法在不同尺寸地图中的表现均较为良好,尤其是在大尺寸地图中,其规划的路径最短且运行时间缩短了20 ms以上,证明该算法具有较强的鲁棒性。

中欧班列多周期干支结合方案图铺画方法研究

目前中欧班列具有多周期、多频次的特点,常以周或日为周期,难以适应以日为周期的铁路列车运行图,存在能力利用不均衡、运行线丢失、运输组织难度大、通道和口岸站阶段能力紧张等问题。提出中欧班列多周期干支结合方案图铺画方法,将方案图铺画问题简化为复杂耦合约束下的局部运力资源分配问题,构建中欧班列多周期干支结合方案图编制模型,以列车自满足发车条件至终到的总时间和列车在中间站的停站总时间等最小化为目标函数,以列车发车时间窗、列车间隔时间、天窗时间、客流高峰时段和干线运力资源分配等为约束条件,设计算例,编制具有周期化、能力均衡利用、运行顺畅等特征的方案图。结果表明:干支结合方案图铺画方法适用于处理多周期复杂交通运输系统的时刻表编制问题,有助于推进中欧班列运行线的固定、周期化开行,均衡利用路网运力资源和按图行车等。

基于Biomod2平台组合模型的蒙古黄芪生产区划研究

目的:分析蒙古黄芪生境适宜性,结合土地利用类型数据,确定其生产适宜区。方法:基于蒙古黄芪的分布数据和包含气候因子、土壤因子等的环境变量数据,采用Biomod2平台组合模型,筛选蒙古黄芪的主要生态因子,构建其生产适宜性综合评价模型。结果:模型评价结果表明,我国东北、华北及西北的大部分地区适宜种植蒙古黄芪,高适宜种植区主要分布在内蒙古中东部、吉林东北部、黑龙江东部、河北北部、甘肃东南部和山西、陕西部分地区。结论:组合模型与单一模型各有优缺点,虽然单一模型中的推进式回归树模型和随机森林模型在精度和面积分布方面均表现较好,但组合模型整体表现优于任意单一模型。因此,组合模型对蒙古黄芪的生产适宜性评价更为精确,可为其生产区划研究提供更好的评价方法。

多网融合背景下都市圈市域(郊)铁路网规划方案评价研究

近年来,国家积极推进轨道交通“多网融合”建设以支撑促进新型城镇化发展,市域(郊)铁路是“多网融合”中的重要联动纽带。为实现市域(郊)铁路的合理科学建设发展,其线网规划至关重要。提出了一种具有普适性的都市圈市域(郊)铁路网规划科学评估方法,以期为都市圈市(域)郊线网及整体轨道交通网络融合建设发展提供决策参考。从多网融合程度、都市圈支撑强度、运营服务能力、方案实施可能四个角度建立多目标评价指标体系,并运用基于信息熵权法和AHP组合赋权法的TOPSIS方法实现规划方案的量化综合评价分析。以福州都市圈核心区为例进行应用分析,结果表明,既有铁路利用程度较高的规划方案最优,最优方案一方面可充分利用铁路运能,实现都市圈交通资源合理配置;另一方面可较好融合都市圈各层次轨道交通,更好地服务于都市圈旅客交流。