A Multi-stage Heuristic Algorithm for Matching Problem in the Modified Miniload Automated Storage and Retrieval System of E-commerce

E-commerce, as an emerging marketing mode, has attracted more and more attention and gradually changed the way of our life. However, the existing layout of distribution centers can＇t fulfill the storage and picking demands of e-commerce sufficiently. In this paper, a modified miniload automated storage/retrieval system is designed to fit these new characteristics of e-commerce in logistics. Meanwhile, a matching problem, concerning with the improvement of picking efficiency in new system, is studied in this paper. The problem is how to reduce the travelling distance of totes between aisles and picking stations. A multi-stage heuristic algorithm is proposed based on statement and model of this problem. The main idea of this algorithm is, with some heuristic strategies based on similarity coefficients, minimizing the transportations of items which can not arrive in the destination picking stations just through direct conveyors. The experimental results based on the cases generated by computers show that the average reduced rate of indirect transport times can reach 14.36% with the application of multi-stage heuristic algorithm. For the cases from a real e-commerce distribution center, the order processing time can be reduced from 11.20 h to 10.06 h with the help of the modified system and the proposed algorithm. In summary, this research proposed a modified system and a multi-stage heuristic algorithm that can reduce the travelling distance of totes effectively and improve the whole performance of e-commerce distribution center.

Unconditionally stable Crank-Nicolson algorithm with enhanced absorption for rotationally symmetric multi-scale problems in anisotropic magnetized plasma

Large calculation error can be formed by directly employing the conventional Yee’s grid to curve surfaces.In order to alleviate such condition,unconditionally stable CrankNicolson Douglas-Gunn(CNDG)algorithm with is proposed for rotationally symmetric multi-scale problems in anisotropic magnetized plasma.Within the CNDG algorithm,an alternative scheme for the simulation of anisotropic plasma is proposed in body-of-revolution domains.Convolutional perfectly matched layer(CPML)formulation is proposed to efficiently solve the open region problems.Numerical example is carried out for the illustration of effectiveness including the efficiency,resources,and absorption.Through the results,it can be concluded that the proposed scheme shows considerable performance during the simulation.

Analytical Structure Matching and Very Precise Approach to the Coulombic Quantum Three—Body Problem

A powerful approach to solve the Coulombic quantum three-body problem is proposed. The approach is exponentially convergent and more efficient than the hypcrsphcrical coordinate method and the correlation-function hyperspherical harmonic method. This approach is numerically competitive with the variational methods, such as that using the Hylleraas-type basis functions. Numerical comparisons are made to demonstrate the efficiency of this approach, by calculating the nonrelativistic and infinite-nuclear-mass limit of the ground state energy of the helium atom. The exponential convergency of this approach is due to the full matching between the analytical structure of the basis functions that are used in this paper and the true wavefunction. This full matching was not reached by most other methods. For example, the variational method using the Hylleraas-type basis does not reflects the logarithmic singularity of the true wavefunction at the origin as predicted by Bartlett and Fock. Two important approaches are proposed in this work to reach this full matching: the coordinate transformation method and the asymptotic series method. Besides these, this work makes use of the lcast square method to substitute complicated numerical integrations in solving the Schrodinger equation without much loss of accuracy, which is routinely used by people to fit a theoretical curve with discrete experimental data, but here is used to simplify thc computation.

An Adaptive Uniaxial Perfectly Matched Layer Method for Time-Harmonic Scattering Problems

The uniaxial perfectly matched layer (PML) method uses rectangular domain to define the PML problem and thus provides greater flexibility and efficiency in deal- ing with problems involving anisotropic scatterers.In this paper an adaptive uniaxial PML technique for solving the time harmonic Helmholtz scattering problem is devel- oped.The PML parameters such as the thickness of the layer and the fictitious medium property are determined through sharp a posteriori error estimates.The adaptive finite element method based on a posteriori error estimate is proposed to solve the PML equa- tion which produces automatically a coarse mesh size away from the fixed domain and thus makes the total computational costs insensitive to the thickness of the PML absorb- ing layer.Numerical experiments are included to illustrate the competitive behavior of the proposed adaptive method.In particular,it is demonstrated that the PML layer can be chosen as close to one wave-length from the scatterer and still yields good accuracy and efficiency in approximating the far fields.

A Note on the Matching Polynomials of Paths and Cycles

The spectra of matching polynomials which are useful in the computations of resonance energy and grand canonical partition functions of molecular's. It also present other properties for certain classes of graphs and lattices. In [1] Balasubramanian calculates several matching polynomials and matching roots of several molecular graphs. He found that the matching polynomial of C_6, C_(10), C_(14), C_(18) and C_(22) are divided by x^2-2. In this note,we prove that x^2-2 divides MC_(4k+2)(x), k = 1, 2,..., n and obtain some other properties of matching polynomials of paths and cycles.

Improved Parallel Processing Function for High-Performance Large-Scale Astronomical Cross-Matching

Astronomical cross-matching is a basic method for aggregating the observational data of different wavelengths. By data aggregation, the properties of astronomical objects can be understood comprehensively. Aiming at decreasing the time consumed on I/O operations, several improved methods are introduced, including a processing flow based on the boundary growing model, which can reduce the database query operations; a concept of the biggest growing block and its determination which can improve the performance of task partition and resolve data-sparse problem; and a fast bitwise algorithm to compute the index numbers of the neighboring blocks, which is a significant efficiency guarantee. Experiments show that the methods can effectively speed up cross-matching on both sparse datasets and high-density datasets.

Game-Theory Analysis for High Satisfaction Matchingon Strategic Decision

In any group,the project’s members want to create the highest value for the common goal,and how to choose project’s members could be a game.This study investigated the cooperating with education institutions.Analysis of the players’strategic choices and relative outcomes was conducted.The researchers would organize a simple tree model and sort to payoff matrix.The results revealed that the strategy of each player is different finally.There were two strategies for selecting a member-'Choosing Good Friendship player'and'Choosing Good Ability player'.Furthermore,this study also analyzed the influencing factors and stable matching possibility among the factors.

求解TSP的离散野马优化算法

针对求解TSP问题,提出一种新的元启发式算法离散野马优化算法(DWHO),应用最小位置匹配值法(MPMV)对求解结果进行离散化解码;为提高算法搜索能力,结合野马放牧、交配、领导者交流与选拔行为,引入变邻域搜索策略,增强了算法的局部搜索能力、加快算法收敛速度。选取TSPLIB标准库33个算例进行实验,并与交换序列人工蜂群算法(ABCSS)、离散蜘蛛猴优化算法(DSMO)两种算法进行比较。实验结果表明,DWHO求得的最优解与ABCSS、DSMO两种算法的最优解相比,最优解改进率最大值分别达到4.52%和3.41%。同时,将离散野马优化算法求解TSP收敛速度与以上两种算法进行比较,其收敛速度具有一定的优势。结果表明离散野马优化算法求解能力和精度具有优势。

基于变形图匹配的知识图谱多跳问答

知识图谱问答(KGQA)是给定自然语言问题,对问题进行语义理解和解析,进而利用知识图谱进行查询、推理得出答案的过程。但知识图谱通常是不完整的,链接缺失给多跳问答带来许多挑战。许多方法在利用知识图谱嵌入时忽略了重要的路径信息来评估路径和多关系问题之间的相关性;且使用文本语料库也会限制文本增强模型的可扩展性。针对这些现有方法的缺陷,提出了基于变形图匹配的知识图谱问答(DGM-KGQA)模型,该模型同时利用问题和主题实体构建语义子图,与知识图谱的局部结构匹配并找到正确答案。在基准数据集MetaQA上的实验结果验证了DGM-KGQA的有效性,该模型在完整知识图谱上检索到的答案准确率分别比PullNet、EmbedKGQA增加了4.2%、0.8%;在完整度仅有一半的知识图谱上检索到的答案准确率分别比PullNet、EmbedKGQA增加了11.1%、0.5%。实验证明提出的变形图匹配模型能够有效地增强知识图谱的关联性及多跳问答的答案准确率。

乡村振兴背景下生鲜农产品上行集货路径优化研究

农产品上行“最先一公里”的集货问题是乡村经济发展中的重要一环,集货的效率直接影响农产品上行运输的经济成本。针对偏远农户集货成本高、集货不便问题,设计考虑农户协作的运输模式,建立协作距离最小化模型,实现偏远农户的协作匹配。在此基础上,以运输成本、货损成本、协作成本最小化为目标,建立农产品上行集货路径优化模型,并设计改进的节约里程-禁忌搜索算法进行求解。最后,案例分析的结果表明,本文所提出的模型和算法是有效的。

M对N型贸易关系的国际集装箱海运服务多目标多边匹配决策研究

国际集装箱海运因其运价低、运距远的特征,对于促进国际贸易、实现全球化生产具有重大意义。针对M对N型贸易关系下的国际集装箱海运服务匹配问题,将匹配指标划分为效益型指标和成本型指标;同时,创新性地采用三方主体在四个匹配环节中匹配满意度的算数平均值来表达整体匹配满意度。在构建最大化匹配主体满意度为目标函数的基础上,还增加对匹配中介收益的考虑,最终将模型转化为类似经典的运输平衡问题。发货人运输给收货人的集装箱数量是在匹配任务开始前根据他们先前订立的贸易合同就已经确定的,是无法改变的,且三方主体之间的匹配满意度不会因为箱量的增减发生线性的变化。因此,在采用最大元素法后获得的初始解即为最优解,无需做调整,也进一步说明本模型的实用性和操作性。

求解online packing problem的F-B绝对近似算法

FF算法由于其在线特性在处理在线装箱问题得到广泛使用,但它无法预测后面达到物品造成装箱率低,提出一种预留一定比例的各类未装满箱体的装箱算法。首先对未装满箱体分类并给出相应的数据结构,接着设计一种绑定配对策略来预留各类未装满箱体数目,并引入间隔函数控制新箱体的启用,最后基于FF算法结合预留策略对物品进行装箱来保证装箱的绝对近似比。提出了一种预留绑定配对策略为后续输入物品提供预测空间,特别的是F-B算法能得到5/3的绝对近似比。

融合知识图谱和语义匹配的医疗问答系统

问答系统是自然语言处理领域中的一项重要任务,常应用于医疗服务。传统的问答系统通过知识图谱的实体关系匹配返回相应的尾实体作为答案,然而,倘若实体或关系无法识别,又或者在知识图谱中并不存在相应的实体关系,问答将无法继续进行。为了解决这一问题,建立一种融合知识图谱和语义匹配模型的中文医疗问答混合系统。当所提问题无法在知识图谱中进行实体关系匹配时,该模型能继续从问答对数据集中找到最相似的问题,并返回相应结果作为答案。在语义匹配模型方面,结合中文医疗相似问题对,在Sentence-BERT模型上进行微调训练,并引入双曲空间中的距离度量函数对句子对进行相似度度量。结果表明:在整体性能方面,所提模型相较于BERT这类大语言模型精度能提升7.16%;在度量能力方面,双曲度量相较于通用欧氏空间度量,如余弦度量,最高能有2.28%的精度提升和1.58%的F_1值提升。

A Class of Singularly Perturbed Nonlinear Shock Problems

用匹配的 asymptotic 扩大的方法，不可思议地使不安的非线性的问题的一个班的吃惊解决方案是吃惊答案和他们的边界条件的 discussed.The 关系是 obtained.And 已知的结果被概括。

A VARIATIONAL PROBLEM ARISING IN REGISTRATION OF DIFFUSION TENSOR IMAGES

The existence of a global minimizer for a variational problem arising in registration of diffusion tensor images is proved, which ensures that there is a regular spatial transformation for the registration of diffusion tensor images.

The Paired Assignment Problem

We consider a variation of the maximum bipartite matching problem where each completed task must have at least two agents assigned to it. We give an integer programming formulation for the problem, and prove that the basic solutions of LP-relaxation are half-integral. It is shown that a fractional basic solution can be further processed to obtain an optimal solution to the problem.

Some Results on Position Restriction Scheduling Problems

在这份报纸，我们首先考虑在单个 machine.The 上安排问题的位置限制问题在某些特殊情况中被解决了，特别因为限制处理时间 pj=1.We 获得的那些介绍由两部组成的匹配算法提供一些多项式时间算法解决我们进一步在无关的处理器上考虑一个问题的 them.Then 。

基于自注意力网络的深度图匹配模型

现有深度图匹配模型在节点特征提取阶段常利用图卷积网络(GCN)学习节点的特征表示。然而,GCN对节点特征的学习能力有限,影响了节点特征的可区分性,造成节点的相似性度量不佳,最终导致模型的匹配精度受损。为解决这一问题,提出一种基于自注意力网络的深度图匹配模型。所提模型在节点特征提取阶段使用新的自注意力网络来学习节点特征,其原理是通过空间编码器和自注意力机制分别学习节点的空间结构以及所有节点之间的联系,从而改善节点的特征描述。此外,为了减小放松图匹配问题所带来的精度损失,将图匹配问题建模为整数线性规划问题,在图匹配问题的节点匹配基础上增加结构匹配约束,以及引入高效的组合优化求解器来计算图匹配问题的局部最优解。实验结果表明,在PASCALVOC数据集上,与PCA-GM相比,所提模型在20类图像上的匹配精度平均值提高了14.8个百分点;在Willow Object数据集上,所提模型在5类图像上的匹配精度平均值提高了7.3个百分点,并且在自行车、植物等目标匹配任务上达到了最佳的效果。

贸易不确定性与上市公司审计质量

贸易不确定性持续上升,对企业的发展经营提出新的挑战。本文以2015-2020年的A股上市公司为样本,运用多期双重差分(DID)模型,将2018-2020年被列入“实体清单”作为外生事件,检验了贸易不确定性对我国相关企业审计质量的影响及机制。研究表明,贸易不确定性能够“倒逼”相关企业提高审计质量。进一步分析发现,贸易不确定性对非“百强事务所”审计的企业、行业集中度高、科技水平低的企业表现了更强的审计质量激励作用,作用机制主要通过减少企业的代理成本和提升媒体关注度来实现。本文探究了贸易不确定性与审计质量的关系,为应对贸易不确定性提供了经验证据。

船舶混合动力推进系统多目标优化研究

为了解决船舶混合动力系统多目标优化难题,采用精确的阻力预测模型及螺旋桨模型预测9000 DWT化学品运输船功率需求。基于推进系统的需求功率,提出基于目标聚类的方法建立多目标优化数学模型,并对系统关键设计参数进行多目标优化研究,对比分析4种典型多目标优化算法对该优化问题的适应性。结果表明:基于快速非支配排序的多目标算法对于含有整数变量、等式约束等混合动力系统多目标优化问题具有良好的鲁棒性和收敛性。采用多目标综合决策求解出的最优设计参数相较于原型船动力系统,最大能效提升约6.1%。