Two-Sided Matching Decision Making with Multi-Attribute Probabilistic Hesitant Fuzzy Sets

In previous research on two-sided matching(TSM)decision,agents’preferences were often given in the form of exact values of ordinal numbers and linguistic phrase term sets.Nowdays,the matching agent cannot perform the exact evaluation in the TSM situations due to the great fuzziness of human thought and the complexity of reality.Probability hesitant fuzzy sets,however,have grown in popularity due to their advantages in communicating complex information.Therefore,this paper develops a TSM decision-making approach with multi-attribute probability hesitant fuzzy sets and unknown attribute weight information.The agent attribute weight vector should be obtained by using the maximum deviation method and Hamming distance.The probabilistic hesitancy fuzzy information matrix of each agent is then arranged to determine the comprehensive evaluation of two matching agent sets.The agent satisfaction degree is calculated using the technique for order preference by similarity to ideal solution(TOPSIS).Additionally,the multi-object programming technique is used to establish a TSM method with the objective of maximizing the agent satisfaction of two-sided agents,and the matching schemes are then established by solving the built model.The study concludes by providing a real-world supply-demand scenario to illustrate the effectiveness of the proposed method.The proposed method is more flexible than prior research since it expresses evaluation information using probability hesitating fuzzy sets and can be used in scenarios when attribute weight information is unclear.

A Novel Symbolic Algorithm for Maximum Weighted Matching in Bipartite Graphs

The maximum weighted matching problem in bipartite graphs is one of the classic combinatorial optimization problems, and arises in many different applications. Ordered binary decision diagram (OBDD) or algebraic decision diagram (ADD) or variants thereof provides canonical forms to represent and manipulate Boolean functions and pseudo-Boolean functions efficiently. ADD and OBDD-based symbolic algorithms give improved results for large-scale combinatorial optimization problems by searching nodes and edges implicitly. We present novel symbolic ADD formulation and algorithm for maximum weighted matching in bipartite graphs. The symbolic algorithm implements the Hungarian algorithm in the context of ADD and OBDD formulation and manipulations. It begins by setting feasible labelings of nodes and then iterates through a sequence of phases. Each phase is divided into two stages. The first stage is building equality bipartite graphs, and the second one is finding maximum cardinality matching in equality bipartite graph. The second stage iterates through the following steps: greedily searching initial matching, building layered network, backward traversing node-disjoint augmenting paths, updating cardinality matching and building residual network. The symbolic algorithm does not require explicit enumeration of the nodes and edges, and therefore can handle many complex executions in each step. Simulation experiments indicate that symbolic algorithm is competitive with traditional algorithms.

IMPROVEMENT AND REALIZATION FOR THE MAXIMUM WEIGHT MATCHING ALGORITHM

Some new concepts of effective incidence matrix,ascending order adjacency matrix andend-result vertex are introduced,and some improvements of the maximum weight matchingalgorithm are made.With this method a computer program in FORTRAN language is realized onthe computers FELIX C-512 and IBM-PC.Good results are obtained in practical operations.

A spherical higher-order finite-difference time-domain algorithm with perfectly matched layer

A higher-order finite-difference time-domain（HO-FDTD） in the spherical coordinate is presented in this paper. The stability and dispersion properties of the proposed scheme are investigated and an air-filled spherical resonator is modeled in order to demonstrate the advantage of this scheme over the finite-difference time-domain（FDTD） and the multiresolution time-domain（MRTD） schemes with respect to memory requirements and CPU time. Moreover, the Berenger＇s perfectly matched layer（PML） is derived for the spherical HO-FDTD grids, and the numerical results validate the efficiency of the PML.

The Symbolic OBDD Algorithm for Finding Optimal Semi-matching in Bipartite Graphs

The optimal semi-matching problem is one relaxing form of the maximum cardinality matching problems in bipartite graphs, and finds its applications in load balancing. Ordered binary decision diagram (OBDD) is a canonical form to represent and manipulate Boolean functions efficiently. OBDD-based symbolic algorithms appear to give improved results for large-scale combinatorial optimization problems by searching nodes and edges implicitly. We present novel symbolic OBDD formulation and algorithm for the optimal semi-matching problem in bipartite graphs. The symbolic algorithm is initialized by heuristic searching initial matching and then iterates through generating residual network, building layered network, backward traversing node-disjoint augmenting paths, and updating semi-matching. It does not require explicit enumeration of the nodes and edges, and therefore can handle many complex executions in each step. Our simulations show that symbolic algorithm has better performance, especially on dense and large graphs.

外卖智能派单的订单-骑手多目标匹配模型及其适应性算法研究

随着外卖业的快速发展,外卖智能派单成为外卖服务的重要形式。然而,目前相关研究侧重于研究外卖配送路径问题,不利于解决外卖智能派单的多目标动态决策中存在的问题。本文从外卖订单-骑手匹配的角度,分析了外卖平台智能派单的五个基本目标和四个基本约束,构建了多目标的订单-骑手匹配优化模型,进而给出了基于适应性策略的实时优化算法。最后,本文设计了外卖智能派单的仿真实验,对比了骑手-订单数量均衡、骑手供过于求、骑手供不应求等三种情况下的优化情况,验证了基于适应性策略的实时优化算法的优化效果。本研究对外卖平台发展智能派单模式具有较好的理论与实践价值。

考虑订单拆分策略的AGV拣选效率优化方法

为提高智能仓库系统中AGV的拣选效率,针对AGV订单拣选优化问题分为AGV-货架任务分配、多AGV无冲突路径规划两个子问题进行研究,根据订单特点引入订单拆分策略,并以最小化AGV完成所有订单的总时间为目标构建数学模型。首先,设计了确定货架优先级的AGV-货架任务分配算法(AGV-shelf task allocation algorithm, ASTA)求解匹配问题。然后,提出一种带有贪婪参数并嵌入冲突消解策略的改进Q-Learning算法,得到拆分策略下最优无冲突拣选路径方案。最后,通过在40 m×40 m仓库布局中的订单集数值实验对比分析,所提算法与现有的两种算法对比结果显示,AGV完成所有订单的总时间分别平均减少11.63%和26.74%,验证了拆分策略的有效性,并且通过AGV使用数量、完成订单时间和路径冲突等待时间占比三个指标的对比验证了拆分策略和所提算法能有效缓解拥堵情况,减少行驶路径长度,提高拣选效率。此外,针对AGV数量灵敏度分析,在不同数量的AGV对行驶时间和路径冲突等待时间的影响方面,发现19台AGV数量是最佳配置,验证了模型的可行性和算法的有效性。

基于马尔可夫决策的钢铁产成品订单分配模型研究

物流订单分配是钢铁产成品销售过程中的重要环节,对销售过程的整体体验和全流程的良性循环起着至关重要的作用。在实际生产过程中,传统的人工分单模式已难以适应长时间维度的发展要求。为了充分考虑一个时间周期内销售的物流成本最低以及承运司机的收益较高,同时确保企业的长期收益,本文用多目标约束,建立马尔可夫决策模型,引入KM算法执行二分图匹配,基于司机收益最大化和企业成本最小的多目标优化,最大化钢铁商品总交易量为长期的最终目标,结合价值函数和多属性的多目标优化函数,形成车辆和货物的完整匹配决策。以钢铁企业的真实业务数据为例,对数据进行预处理后筛选合适特征进行模型训练并验证算法的正确性和可用性。结果表明,该模型相较于传统的订单分配方法,可以更好地解决钢铁企业在订单分配场景下的需求。

联合高阶目标感知与相似匹配的目标跟踪算法

视觉目标跟踪算法利用自注意力机制增强上下文联系,但面对复杂场景时,自注意力机制中的相关性易发生失配,为此提出一种联合高阶目标感知与相似匹配的目标跟踪算法。构建高阶目标感知模型,针对自注意力机制中的一阶自注意图,利用坍塌的极化过滤方式进行空间和通道维度的正交化建模,优化内部相关性;同时组合非线性拟合函数避免坍塌引起的信息损失,进而获得高阶自注意图,捕获具有高阶上下文信息的感知特征。通过不同维度分解目标的感知特征来细化匹配区域,抑制背景噪声并约束当前帧的响应图,提高网络的判别力。在OTB100和UAV123基准的实验结果表明,所提算法有更好的跟踪性能,可以有效应对相似干扰等问题。

基于知识共享的遮挡人体姿态估计网络

现有人体姿态估计方法处理遮挡情况时性能较差,为此提出新的估计网络,包含遮挡区域强化卷积网络(OCNN)和遮挡特征补偿图卷积网络(OGCN).设计高低阶特征匹配注意力以强化遮挡区域特征,由OCNN提取高适配权重,通过少量遮挡数据的方式实现遮挡部位的强化检测.由OGCN消除障碍物特征,通过强化关键点共有及专有属性的方式补偿节点特征;进行邻接矩阵重要性加权以改善遮挡部位特征质量,提升检测精度.所提网络在数据集COCO2017、COCO-Wholebody、CrowdPose上的检测精度分别为78.5%、67.1%、77.8%,优于对比算法.在自建遮挡数据集上所提网络节约了75%的训练数据使用.

基于通用化等效模型的飞机系统辨识算法

针对舰载机等复杂动力学系统的高阶时滞模型拟配难题,提出了一种基于通用化等效模型的系统频域辨识算法。建立系统辨识通用化等效模型,引入自适应学习率梯度下降法对模型进行基于样本的迭代学习训练,使模型的频域参数自动收敛,辨识得到复杂系统的高阶时滞模型。以舰载机横航向荷兰滚等效拟配模型进行验证,与传统算法对比,并分析了系统的频域与时域响应,结果表明:所提算法具有较好的辨识效果,解决了高阶时滞模型的直接拟配难题,并通用于广泛的高阶时滞模型拟配。

三色激光在充气波导管内产生孤立阿秒脉冲相位匹配条件的分析(特邀)

对比优化与未优化的三色光组合发现,当高次谐波场在波导管内传播时,仅当单原子响应中始终保持单个发射峰,或者在合适相位匹配条件下单原子响应中的多余发射峰被抑制时,才能有效地产生孤立阿秒脉冲。比较不同三色光组合下产生的孤立阿秒脉冲的性能,确定基频激光(1600 nm)与其二倍频场(800 nm)、四倍频场(400 nm)的优化组合是在波导管内产生孤立阿秒脉冲的最佳组合。

网络货运模式车货匹配问题研究现状综述

网络货运是当前物流行业中一种新兴货物运输模式,其不仅推动了物流行业的变革,也给物流行业带来了新的机遇和挑战。车货匹配环节的效率直接影响到整体物流的效能。因此,文章通过文献统计和文献总结分析的方法,系统评述了订单整合问题、车辆配载问题的数学建模及求解算法。研究发现:车货匹配问题在理论研究和实际应用方面均取得了显著进展,但在结合人工智能、大数据等新兴技术方面的应用尚显不足。文章对两类问题主要研究内容及方法做了简要总结,并对车货匹配问题未来研究方向进行了展望。

工艺管线高效预制方案探讨

工艺管线材料种类繁多、建造工艺复杂、检验要求高,车间预制需优化图纸材料前端输入,施工过程加强管控,通过简化工序流程和提高焊接、检验效率的方式,达到快速释放的目的。采用预制前图料匹配、工单精准配送、高效管线组对工艺与自动焊接等施工措施,可加快管线预制施工效率。生产管理系统、PAUT及批次放行等现代化检验方式的应用,在保障产品质量的同时,缩短了检验周期。

完全匹配层在矩阵式波动方程SBP-SAT方法应用

数值离散方法和截断边界效果是地震动模拟实现的关键。基于分部求和(summation-by-parts,SBP)和一致逼近(simultaneous approximation term,SAT)的SBP-SAT方法具有较高的稳定性,这使得该方法具备了较高的应用前景和价值。此外,完全匹配层(perfect matching layer,PML)是一种应用广泛用于模拟截断边界的技术,但引入匹配层可能会破坏原始方程的稳定性,特别是在各向异性介质或曲线域模型中。首先基于数理推导,给出弹性波动方程系数矩阵的对称形式。在此基础上,引入多轴完全匹配层(multi-axis perfect matching layer,MPML),并建立相应的匹配层方程。通过本征值分析,我们可以判断阻尼函数对原方程特征根实部的走向和取值范围的影响。然后,我们采用SBP-SAT方法对矩阵对称形式匹配层方程进行离散,并在频域中采用能量法进行稳定性评估。通过对不同模型的数值仿真,表明所提出的离散框架具有整合度高、稳定性好和拓展性强等特点。此外,多轴匹配层可以与SBP-SAT方法结合,可以稳定地模拟曲线域中的波传播。

秩序知觉理论下的当代舞剧视觉焦点探论

艺术创作与审美活动离不开艺术家对规则与秩序建立的探求。预先匹配机制是舞蹈艺术创作建立秩序的重要手段,它揭示了主体在舞蹈审美活动中对视觉焦点选择的内在规律,帮助创作者透过秩序知觉原则筑造符合观者审美心理规律的舞蹈图像。从时空力的拆解与重构、情境配景的虚化与概括、舞台视觉的中断与反差效应等现象剖析舞蹈视觉式样,有助于为当代舞剧视觉焦点的建构提供更丰富的艺术表现方式。

薄厚优劣煤层的配采方案设计与效益分析

针对大阳煤矿井田内3号煤层优质资源已濒临枯竭,在全部开采完结再进行新的煤层资源开发,难以保证矿井的正常接续和生产衔接,影响矿井的后续经营与可持续发展等问题,对大阳煤矿3号、15号可采煤层进行了研究分析,提出了“中厚-厚煤层、高-低硫分、高-低热量”的配采方案。通过线性规划理论,使用二元一次方程组的联合求解方式计算得出最佳配采比例,确定了3、15号煤层2:1的配采方案。方案确定后,利用井下原有生产系统,新建一处西回风立井开采,并对运输设备进行了选择,实现了高热量、低硫分的配煤生产,具有更优的经济价值,在保证矿井1.80 Mt/a稳定生产的同时,延长了矿井服务年限。

Thermoelastic Analysis of Non-uniform Pressurized Functionally Graded Cylinder with Variable Thickness Using First Order Shear Deformation Theory(FSDT) and Perturbation Method

Recently application of functionally graded materials（FGMs） have attracted a great deal of interest. These materials are composed of various materials with different micro-structures which can vary spatially in FGMs. Such composites with varying thickness and non-uniform pressure can be used in the aerospace engineering. Therefore, analysis of such composite is of high importance in engineering problems. Thermoelastic analysis of functionally graded cylinder with variable thickness under non-uniform pressure is considered. First order shear deformation theory and total potential energy approach is applied to obtain the governing equations of non-homogeneous cylinder. Considering the inner and outer solutions, perturbation series are applied to solve the governing equations. Outer solution for out of boundaries and more sensitive variable in inner solution at the boundaries are considered. Combining of inner and outer solution for near and far points from boundaries leads to high accurate displacement field distribution. The main aim of this paper is to show the capability of matched asymptotic solution for different non-homogeneous cylinders with different shapes and different non-uniform pressures. The results can be used to design the optimum thickness of the cylinder and also some properties such as high temperature residence by applying non-homogeneous material.

Unsplit-field higher-order nearly PML for arbitrary media in EM simulation

An unsplit-field higher order nearly perfectly matched layer(NPML)based on the auxiliary differential equation approach is introduced in three-dimensional finite-difference timedomain lattices.The proposed scheme has the advantage of both the NPML scheme and the higher order concept in terms of the improved absorbing performance and considerable computational efficiency.By incorporating with the generalized material independent concept,the proposed implementation is indepen dent of the material’s type.Thus,it has the advantages of terminating arbitrary media without changing the updated equations in the PML regions.Its effectiveness and efficiency is further demonstrated through numerical examples.

Model Order Reduction for Coupled Dynamic Characterization of Torsional Micromirrors

Numerical solutions could not perform rapid system-level simulation of the behavior of micro-electro-mechanical systems（MEMS） and analytic solutions for the describing partial differential equations are only available for simple geometries.Model order reduction（MOR） can extract approximate low-order model from the original large scale system.Conventional model order reduction algorithm is based on first-order system model,however,most structure mechanical MEMS systems are naturally second-order in time.For the purpose of solving the above problem,a direct second-order system model order reduction approach based on Krylov subspace projection for the coupled dynamic study of electrostatic torsional micromirrors is presented.The block Arnoldi process is applied to create the orthonormal vectors to construct the projection matrix,which enables the extraction of the low order model from the discretized system assembled through finite element analysis.The transfer functions of the reduced order model and the original model are expanded to demonstrate the moment-matching property of the second-order model reduction algorithm.The torsion and bending effect are included in the finite element model,and the squeeze film damping effect is considered as well.An empirical method considering relative error convergence is adopted to obtain the optimal choice of the order for the reduced model.A comparison research between the full model and the reduced model is carried out.The modeling accuracy and computation efficiency of the presented second-order model reduction method are confirmed by the comparison research results.The research provides references for MOR of MEMS.