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.     

基于遗传萤火虫算法的含风电电力系统机组组合研究

随着风能资源的广泛应用,机组组合问题求解愈显复杂。以减少煤耗费用提高系统经济性为目标,提出一种采用遗传萤火虫算法求解含风电电力系统机组组合问题的新方法。引入遗传算法双矩阵通路判断及约束修复策略,提高了初始解生成质量及产生速度;再利用萤火虫算法求解连续负荷经济优化分配,给出自适应交叉概率,从而提高了算法的收敛速度。应用所提算法对经典10机系统优化仿真表明,与其他算法相比,该方法能合理安排机组组合,提高系统供电的经济性,具有较好的实用价值。     

Significant population genetic structuring in Rhyzopertha dominica across Turkey: Biogeographic and practical implications

Rhyzopertha dominica is a key pest of stored grain. Understanding the movement of this beetle on broad geographic scales is crucial, particularly when developing strategies to prevent the spread of phosphine resistance. We assessed population genetic structuring in this pest across Turkey, using a combination of mitochondrial (cytochrome oxidase I) and microsatellite markers. In addition, we screened samples for Wolbachia, as this endosymbiont has previously been suggested to be associated with low mitochondrial genetic diversity in this beetle. Mitochondrial genetic diversity was low, with only six haplotypes identified. The genetic diversity was, however, substantially higher than that previously found in Australia or India, suggesting that R. dominica may have originated in the Middle East. Wolbachia were detected only at a single site, indicating they are not impacting the mitochondrial genetic diversity of R. dominica across Turkey. Microsatellite markers indicated there is significant geographic genetic structuring across Turkey, even among sites less than 100 km apart, suggesting there is little movement of beetles across regions within the country. This contrasts with the significantly higher levels of gene-flow found in Australia and the United States. We suggest that the limited movement of beetles across Turkey may be due to a combination of the historically localised agricultural practices (which limits anthropogenic movement among regions), and the mountainous landscape (which limits active flight among regions). Our results demonstrate that the movement of stored product pests may differ significantly across studies conducted in different countries. As a consequence, phosphine resistance management strategies must incorporate region specific information on the extent of beetle movement.     

Distributed privacy protection strategy for MEC enhanced wireless body area networks

With the rapid development and widespread application of Wireless Body Area Networks (WBANs), the traditional centralized system architecture cannot handle the massive data generated by the edge devices. Meanwhile, in order to ensure the security of physiological privacy data and the identity privacy of patients, this paper presents a privacy protection strategy for Mobile Edge Computing(MEC) enhanced WBANs, which leverages the blockchain-based decentralized MEC paradigm to support efficient transmission of privacy information with low latency, high reliability within a high-demand data security scenario. On this basis, the Merkle tree optimization model is designed to authenticate nodes and to verify the source of physiological data. Furthermore, a hybrid signature algorithm is devised to guarantee the node anonymity with unforgeability, data integrity and reduced delay. The security performance analysis and simulation results show that our proposed strategy not only reduces the delay, but also secures the privacy and transmission of sensitive WBANs data.     

黄河万家寨河段河冰冰厚遥感提取及年内变化特征分析

冰凌观测是防凌的前提,是冰凌研究的基础,因此全面准确的冰凌观测可为科学防凌提供可靠的依据。为此,以黄河万家寨库区河段为例,通过冰厚反演算法对其冰厚数据进行遥感反演,利用Lebedev模型对反演结果进行验证,并对结果进行年内变化特征分析。结果表明,卫星遥感反演结果与实测及模型验证结果接近,相关系数为0.8;冰厚演变总体呈成冰、流凌、初封、稳封、融冰、开河的生消演变过程。反演冰厚结果可为黄河内蒙段防凌减灾等实际工作提供参考依据。