基于克里金理论的辐射剂量场插值重构与可视化研究

使用基于克里金理论的插值计算方法对均匀网格与随机排列等不同分布类型的辐射剂量场进行了数据重构与可视化研究,并将重构结果与常用的反距离加权插值法进行了对比,分析了不同插值方法对辐射剂量场重构精度与可视化显示效果的影响。结果表明:对于多数情况,克里金插值法在辐射剂量场重构的精度与可视化显示的效果上均明显优于反距离加权插值法,算例中克里金插值法的结果与原始数据之间的偏差在10%以内,而反距离加权插值法的结果与原始数据之间的偏差基本在15%以上;但在辐射剂量场梯度变化较大且已知数据极少的区域,克里金插值法的计算结果偏差会增大,此时可使用反距离加权插值作为其补充,综合使用。本文的研究工作,验证了克里金插值法在辐射剂量场重构与可视化方面的应用潜力,可为推动辐射剂量场可视化仿真技术的发展提供技术支持。     

Generalised multivariable supertwisting algorithm

The purpose of this paper is to present an extension of the generalised supertwisting algorithm (STA) to the multivariable framework. We begin by introducing an algorithm that may be deemed as a linear, quasicontinuous, or discontinuous multivariable system, depending on the functions that define them. For the class represented by such an algorithm we prove the robust, Lyapunov stability of the origin and characterise the perturbations that preserve its stability. In particular, when its vector field is discontinuous or quasicontinuous our algorithm is endowed with finite‐time stability. Due to its resemblance to the scalar case, we denote such finite‐time stable systems as generalised multivariable STA. Furthermore, the class of finite‐time stable systems comprise the currently available versions of STAs. To finalise, by means of simulation examples, we show that our proposed finite‐time stable algorithms are well suited for signals online differentiation and highlight their dynamical traits.     

基于博弈分析的流域水资源配置

针对传统规划方法难以体现水资源配置过程中多种复杂因素的问题,基于博弈理论建立宏观调控和市场经济相结合的水资源配置动态博弈模型,求解其子博弈精炼纳什均衡下各博弈参与人的策略,并运用改进量子遗传算法求解该博弈模型。对A河流域水资源配置结果表明,在保证流域公共生态用水2.0×10~8 m~3的基础上,各用水子区自发约束自身的取水量,达到均衡时,社会总收益为11.27亿元,相比自由取水模型,社会总收益增加了0.95亿元,增幅为9.2%。     

Hierarchical Learning Water Cycle Algorithm

In order to improve the global searching ability of Water Cycle Algorithm (WCA), the hierarchical learning concept is introduced and the Hierarchical Learning WCA (HLWCA) is proposed in this paper. The underlying idea of HLWCA is to divide the solutions into collections and give these collections with hierarchy differences. One of the collections has a higher hierarchy than others and utilizes an exploration-inclined updating mechanism. The solutions in this high hierarchy collection are the exemplars of other collections. The other collections are sorted according to the exemplars’ function value and the solutions in these collections actively choose whether to follow their own exemplar or not. Through different updating mechanisms of collections, the global searching ability is improved while the fast convergence and strong local search ability of WCA are retained. The proposed HLWCA is firstly experimented on IEEE CEC 2017 benchmark suite to testify its performance on complex numerical optimization tasks. Then, it is tested on four practical design benchmark problems to verify its ability of solving real-world problems. The experimental results illustrate the efficiency of the proposed algorithm.     

Probabilistic tree-based representation for solving minimum cost integer flow problems with nonlinear non-convex cost functions

The minimum cost flow problem (MCFP) is the most generic variation of the network flow problem which aims to transfer a commodity throughout the network to satisfy demands. The problem size (in terms of the number of nodes and arcs) and the shape of the cost function are the most critical factors when considering MCFPs. Existing mathematical programming techniques often assume the cost functions to be linear or convex. Unfortunately, the linearity and convexity assumptions are too restrictive for modelling many real-world scenarios. In addition, many real-world MCFPs are large-scale, with networks having a large number of nodes and arcs. In this paper, we propose a probabilistic tree-based genetic algorithm (PTbGA) for solving large-scale minimum cost integer flow problems with nonlinear non-convex cost functions. We first compare this probabilistic tree-based representation scheme with the priority-based representation scheme, which is the most commonly-used representation for solving MCFPs. We then compare the performance of PTbGA with that of the priority-based genetic algorithm (PrGA), and two state-of-the-art mathematical solvers on a set of MCFP instances. Our experimental results demonstrate the superiority and efficiency of PTbGA in dealing with large-sized MCFPs, as compared to the PrGA method and the mathematical solvers.     

基于改进人工蜂群算法的多目标绿色柔性作业车间调度研究

针对多目标绿色柔性作业车间调度问题（MGFJSP）的特点，提出从碳排放量、噪声和废弃物这3个指标来综合评定环境污染程度，建立了以最小化最大完成时间和环境污染程度为优化目标的MGFJSP模型，并提出了一种改进的人工蜂群算法来求解该模型。算法的具体改进包括：设计了一种三维向量的编码和对应解码方案，在跟随蜂搜索阶段引入一种有效的动态邻域搜索操作来提高算法的局部搜索能力，在侦查蜂阶段提出产生新食物源的策略用于增加种群的多样性。最后进行了实验研究与算法对比，以验证所建模型和所提算法的有效性。     

A Methodology for Modeling and Optimizing Social Systems

Abstract

A system methodology for modeling and optimizing social systems is presented. It allows constructing dynamical models formulated stochastically, i.e., their results are given by confidence intervals. The models provide optimal intervention ways to reach the stated objectives. Two optimization methods are used: (1) to test strategies and scenarios and (2) to optimize with a genetic algorithm. The application case presented is a small nonformal education Spanish business. First, the model is validated in the 2008–2012 period, and subsequently, the optimal way to obtain a maximum profit in the 2013–2025 period is obtained using the two methods.     

MW级空间核反应堆系统热管式辐射散热器分析及优化

空间核反应堆是空间核电源和核推进的研究基础，大功率核反应堆的体积和质量一直是限制航空航天设计的重要因素。针对这一问题，本文对MW级空间核反应堆系统热管式辐射散热器进行建模和分析，建立热管式辐射散热器的热阻模型，利用穷举法和遗传算法在给定工况下探讨裸碳纤维翅片长度L_f和厚度δ_f、冷却剂质量流量m、辐射散热器入口温度T_f1对散热器质量M的影响。结果表明，当T_f1＝800 K、L_f＝5 cm、δ_f＝0.16 mm、m＝9 kg/s时，M达到最优，为906.593 kg，优化了0.63%的系统质量。     

SCMA场景下的极化码编解码方案改进研究

极化码是目前唯一一种被证明可达到信道容量的编码方式,稀疏码分多址接入(Sparse Code Division Multiple Access,SCMA)可以提高频谱资源的利用率和接入系统的用户接入数量。为了提升SCMA与极化码的联合系统的误码率性能和译码时延,使联合系统的应用越来越广泛,提出了2种降低译码复杂度的方式:简化的左信息更新方式和剪枝译码算法。简化的左信息更新方式对于N=256,N=1024的极化码分别能降低37.6%和44.6%的存储资源占用数;剪枝译码算法在码率为0.5时能降低50%左右的计算复杂度。基于简化的SCAN算法改进了联合检测译码算法,在接收机采用外循环迭代的结构,引入了阻尼机制,选取最优的阻尼方式和最优阻尼值。仿真分析了所提联合检测译码算法与原有联合检测译码算法的误码率性能差异,外迭代接收机性能与内外双循环迭代的接收机性能相同,采用阻尼机制联合接收机的性能比无阻尼接收机的性能高0.8 dB左右,SJIDD的误帧率性能比保留宽度为32的SCLJDD的性能低0.7 dB左右,但能使接收机处理时延降至原来的1/4~1/8。     

Power flow calculation for a distribution system with multi-port PETs: an improved AC-DC decoupling iterative method

Recently, power electronic transformers (PETs) have received widespread attention owing to their flexible networking, diverse operating modes, and abundant control objects. In this study, we established a steady-state model of PETs and applied it to the power flow calculation of AC–DC hybrid systems with PETs, considering the topology, power balance, loss, and control characteristics of multi-port PETs. To address new problems caused by the introduction of the PET port and control equations to the power flow calculation, this study proposes an iterative method of AC–DC mixed power flow decoupling based on step optimization, which can achieve AC–DC decoupling and effectively improve convergence. The results show that the proposed algorithm improves the iterative method and overcomes the overcorrection and initial value sensitivity problems of conventional iterative algorithms.