资源受限下森林火灾应急救援多目标调度优化

许多森林火灾由于救援资源受限而不能在第一时间扑灭,导致火灾扩大蔓延,进而造成更大的森林资源损失。因此,在救援资源受限情形下,如何对消防救援车辆进行合理的调度安排以快速和低成本地扑灭火灾已成为亟待解决的现实问题。本文研究了一类资源受限下森林火灾应急救援多目标调度优化问题,为该问题构建了多目标混合整数非线性规划模型,优化目标为同时最小化总灭火救援时间和救援车辆总行驶距离。为有效求解该问题,首先将上述非线性模型等价转化为线性模型。然后提出ε-约束法和模糊逻辑相结合的算法对问题进行求解。最后,以大兴安岭山发生的火灾案例和随机生成仿真算例对模型和算法有效性进行验证,结果表明所提出的模型和算法能够有效解决资源受限下森林火灾应急救援问题,并为决策者提供最优的消防调度方案。     

Tensor train completion: Local recovery guarantees via Riemannian optimization

In this work, we estimate the number of randomly selected elements of a tensor that with high probability guarantees local convergence of Riemannian gradient descent for tensor train completion. We derive a new bound for the orthogonal projections onto the tangent spaces based on the harmonic mean of the unfoldings' singular values and introduce a notion of core coherence for tensor trains. We also extend the results to tensor train completion with auxiliary subspace information and obtain the corresponding local convergence guarantees.     

A deep neural network-based method for solving obstacle problems

In this paper, we propose a method based on deep neural networks to solve obstacle problems. By introducing penalty terms, we reformulate the obstacle problem as a minimization optimization problem and utilize a deep neural network to approximate its solution. The convergence analysis is established by decomposing the error into three parts: approximation error, statistical error and optimization error. The approximate error is bounded by the depth and width of the network, the statistical error is estimated by the number of samples, and the optimization error is reflected in the empirical loss term. Due to its unsupervised and meshless advantages, the proposed method has wide applicability. Numerical experiments illustrate the effectiveness and robustness of the proposed method and verify the theoretical proof.     

Energy-efficient beamforming optimization for MISO communication based on reconfigurable intelligent surface

Reconfigurable intelligent surface (RIS), a planar metasurface consisting of a large number of low-cost reflecting elements, has received much attention due to its ability to improve both the spectrum and energy efficiency (EE) by reconfiguring the wireless propagation environment. In this paper, we propose a base station (BS) beamforming and RIS phase shift optimization technique that maximizes the EE of a RIS-aided multiple-input–single-output system. In particular, considering the system circuits’ energy consumption, an EE maximization problem is formulated by jointly optimizing the active beamforming at the BS and the passive beamforming at the RIS, under the constraints of each user’ rate requirement, the BS’s maximal transmit power budget and unit-modulus constraint of the RIS phase shifts. Due to the coupling of optimization variables, this problem is a complex non-convex optimization problem, and it is challenging to solve it directly. To overcome this obstacle, we divide the problem into active and passive beamforming optimization subproblems. For the first subproblem, the active beamforming is given by the maximum ratio transmission optimal strategy. For the second subproblem, the optimal phase shift matrix at the RIS is obtained by exploiting sine cosine algorithm (SCA). Moreover, for this case where each reflection element’s working state is controlled by a circuit switch, each reflection element’s switch value is optimized with the aid of particle swarm optimization algorithm. Finally, numerical results verify the effectiveness of our proposed algorithm compared to other algorithms.     

优化设计理论在抗滑桩工程中的应用

采用数学规划方法中的直接最优化方法———复合形法,对已知荷载或内力的抗滑桩,以结构成本为目标函数进行满足工程使用要求的有约束最优化设计,编制了相应的程序,并用VisualBasic6 .0开发了应用程序界面,将优化以后所得结果与使用传统设计方法结果比较,有较大降低结构成本的效果。     

The topological optimization for truss structures with stress constraints based on the exist-null combined model

A new exist-null combined model is proposed for the structural topology optimization. The model is applied to the topology optimization of the truss with stress constraints. Satisfactory computational result can be obtained with more rapid and more stable convergence as compared with the cross-sectional optimization. This work also shows that the presence of independent and continuous topological variable motivates the research of structural topology optimization. The project supported by the State Key Laboratory for Structural Analysis of Industrial Equipment, Dalian University of Technology.     

对实心弹性薄板优化的进一步讨论

回顾了实心弹性薄板优化研究的发展历程。给出了由无限密和无限细的肋骨加强的环板在常肋骨密度时的解析解；采用精确刚度阵的有限元法计算了具有有限根肋骨加强的板的柔顺性，它低于光滑优化解的柔顺性。这些结果进一步说明近期文献中出现的枕头形的光滑解并不是几何受约束实心弹性薄板优化问题的全局最优解。     

用反向渐进结构优化方法研究洞室支护优化

洞室开挖支护的优化是在铁路隧道、矿山开挖、水电站建设中经常面对的课题,特别是研究洞室开挖支护拓扑优化有着重要的意义。本文利用近年来发展的渐进优化方法(ESO)的概念,提出了反向ESO方法的迭代格式,建立了洞室开挖支护优化的准则及其敏感度,研究了均匀地基不同地应力条件使得开挖卸荷产生的总应变能最小的最优支护拓扑。结果证明了反向ESO方法的适用性,最优支护拓扑大致成椭圆或者圆形,其主轴方向与最大主应力主轴方向相同。     

结构综合的曲线寻优近似解析方法

本文首次在结构优化领域应用曲线寻优近似解析方法，数值实验表明本文方法的效率较高     

模糊环境下多目标结构动力优化设计

考虑结构设计变量和多阶固有频率优化目标都具有模糊性，以适当方式形成了它们各自的隶属函数。顾及多阶固有频率目标和设计变量约束的最优性隶属程度，构造了多阶固有频率优化的模糊判决函数。形成了模糊环境下结构多阶固有频率动力优化设计方法。以空间杵架算例验证该方法的合理性和有效性。