Parallel Multipopulation Differential Evolutionary Particle Swarm Optimization for Voltage and Reactive Power Control

This paper presents parallel multipopulation differential evolutionary particle swarm optimization (DEEPSO) for voltage and reactive power control (VQC). The problem can be formulated as a mixed integer nonlinear optimization problem and various evolutionary computation techniques have been applied to the problem including PSO, differential evolution (DE), and DEEPSO. Since VQC is one of the online controls, speed‐up of computation is required. Moreover, there is still room for improvement in solution quality. This paper applies parallel multipopulation DEEPSO in order to speed up the calculation and improve solution quality. The proposed method is applied to IEEE 30, 57, and 118 bus systems. The results indicate that the proposed method can realize fast computation and minimize more active power losses than the conventional evolutionary computation techniques.     

绿色住区参数化优化设计平台的开发进展与展望

绿色住区设计是建设宜居城市和实现节能减排目标的重要手段与方法。文章首先回顾绿色住区参数化优化设计方法及平台概况，在此基础上，重点介绍平面生成、噪声计算、通风计算、可视度计算等新增功能和天空遮挡算法升级，以及广州市的工程应用，最后展望平台研发与应用的未来发展方向。     

基于分解的多目标花朵授粉算法

在过去几十年里，许多多目标进化算法被广泛应用于解决多目标优化问题，其中一种比较流行的多目标进化算法是基于分解的多目标进化算法(MOEA/D)。花朵授粉算法是一种启发式优化算法，但迄今为止，花朵授粉算法在基于分解的多目标进化算法领域的研究还非常少。本文在基于分解的多目标进化算法的框架下，将花朵授粉算法拓展至多目标优化领域，提出一种基于分解的多目标花朵授粉算法(MOFPA/D)。此外，为了保证非支配解的多样性，本文提出一种基于网格的目标空间分割法，该方法从找到的Pareto最优解集中筛选出一定数量且分布均匀的Pareto最优解。实验结果表明，基于分解的多目标花朵授粉算法在收敛性与多样性方面均优于基于分解的多目标进化算法。     

Virtual shopping and unconscious persuasion: The priming effects of avatar age and consumers’ age discrimination on purchasing and prosocial behaviors

This study examined how operating elderly or young avatars affected shoppers’ product perceptions and purchasing behaviors. It also investigated how virtual shopping experiences translated into prosocial behavior regarding a nonprofit organization supporting the elderly. Operating elderly avatars influenced shoppers’ product choice and walking speed while shopping compared to operating younger avatars. In addition, operating elderly avatars positively affected participants’ attitudes and willingness to donate to and volunteer for a nonprofit organization supporting the elderly. Statistical interactions between avatar age and a shopper’s ageism on behavioral and persuasion outcomes were also confirmed, and these findings implied an assimilation/contrast effect influenced by a shopper’s preexisting prejudices toward the elderly.     

A stochastic evolutionary coalition game model of secure and dependable virtual service in Sensor-Cloud

Various intrusion detection systems (IDSs) have been proposed in recent years to provide safe and reliable services in cloud computing. However, few of them have considered the existence of service attackers who can adapt their attacking strategies to the topology-varying environment and service providers’ strategies. In this paper, we investigate the security and dependability mechanism when service providers are facing service attacks of software and hardware, and propose a stochastic evolutionary coalition game (SECG) framework for secure and reliable defenses in virtual sensor services. At each stage of the game, service providers observe the resource availability, the quality of service (QoS), and the attackers’ strategies from cloud monitoring systems (CMSs) and IDSs. According to these observations, they will decide how evolutionary coalitions should be dynamically formed for reliable virtual-sensor-service composites to deliver data and how to adaptively defend in the face of uncertain attack strategies. Using the evolutionary coalition game, virtual-sensor-service nodes can form a reliable service composite by a reliability update function. With the Markov chain constructed, virtual-sensor-service nodes can gradually learn the optimal strategy and evolutionary coalition structure through the minimax-Q learning, which maximizes the expected sum of discounted payoffs defined as QoS for virtual-sensor-service composites. The proposed SECG strategy in the virtual-sensor-service attack-defense game is shown to achieve much better performance than strategies obtained from the evolutionary coalition game or stochastic game, which only maximizes each stage's payoff and optimizes a defense strategy of stochastic evolutionary, since it successfully accommodates the environment dynamics and the strategic behavior of the service attackers.     

Multi-objective optimization of shield construction parameters based on random forests and NSGA-II

Metro shield construction will inevitably cause changes in the stress and strain state of the surrounding soil, resulting in stratum deformation and surface settlement (SS), which will seriously endanger the safety of nearby buildings, roads and underground pipe networks. Therefore, in the design and construction stage, optimizing the shield construction parameters (SCP) is the key to reducing the SS rate and increasing the safe driving speed (DS). However, optimization of existing SCP are challenged by the need to construct a unified multiobjective model for optimization that are efficient, convenient, and widely applicable. This paper innovatively proposes a hybrid intelligence framework that combines random forest (RF) and non-dominant classification genetic algorithm II (NSGA-II), which overcomes the shortcomings of time-consuming and high cost for the establishment and verification of traditional prediction models. First, RF is used to rank the importance of 10 influencing factors, and the nonlinear mapping relationship between the main SCP and the two objectives is constructed as the fitness function of the NSGA-II algorithm. Second, a multiobjective optimization framework for RF-NSGA-II is established, based on which the optimal Pareto front is calculated, and reasonable optimized control ranges for the SCP are obtained. Finally, a case study in the Wuhan Rail Transit Line 6 project is examined. The results show that the SS is reduced by 12.5% and the DS is increased by 2.5% with the proposed framework. Meanwhile, the prediction results are compared with the back-propagation neural network (BPNN), support vector machine (SVM), and gradient boosting decision tree (GBDT). The findings indicate that the RF-NSGA-II framework can not only meet the requirements of SS and DS calculation, but also used as a support tool for real-time optimization and control of SCP.     

建筑工业化发展的多群体演化博弈与仿真研究

新型建筑工业化具有高质量、低消耗、可循环发展等特征，其推广已上升到国家战略层面。利用演化博弈方法，建立“政府-开发商-银行” 的三方动态演化博弈模型，进行各博弈主体策略的演化稳定性分析，并针对初始状态、奖惩力度、借贷风险和开发成本等对演化结果的影响进行动态仿真。在此基础上， 考虑开发商群体的网络拓扑特征对演化真实性的影响，引入复杂网络理论， 以无标度网络为载体描述开发商个体的连接偏好和决策机制，构建政府监管下的建筑工业化扩散模型，并通过仿真深入研究相关因素对扩散深度的影响作用，最后结合仿真结果给出相应对策建议。     

Colored apparel and its potential influence on heterosexual attraction

The objective of this study is to determine if men would follow the “red effect” when choosing colors for women to wear on a date, and also to determine if the colors that men would wear when going on a date would be the same as the colors that females (their date) would wish them to wear. A set of psychophysical data was generated from this experiment, where participants were asked to rank a set of 10 colored samples based on preference for each question asked. There were three different sets of colored samples. The set of colored samples given to the participant depended on the question. A total of five questions were asked. Scaling analysis was done on the data to organize a set of items according to preferences providing values, an interval scale (Z values), that correspond to the relative perceptual differences among the stimuli. The Z values were graphed to show the general preference of colors for women to wear, and the preference of colors for men to wear. A Spearman's rank-order correlation coefficient (SRCC) was calculated comparing each individual's rank order with the mean rank order for that specific question. An average Spearman's rank order was calculated for each question and each gender in order to determine the variability in answers. Scaling results indicate that men follow the “red effect,” but women preferred to wear other colors such as turquoise, blue, or yellow depending on the outfit. Males and females agreed that no matter the colored bottoms (denim or black), blue was the preferred color top for men to wear. SRCC results showed a lot of variability between individual answers and the mean answer indicating that participants' rankings did not necessarily agree with general color preferences presented in the scaling analysis. While scaling analysis might suggest certain color preferences such as men following the “red effect” and women preferring to wear blue, the poor correlation found using SRCC between the individual answers and the mean rank orders suggests that color preferences for each individual are inherently unique.     

调水工程水源区与受水区利益演化博弈分析

水源区和受水区是调水工程水质保障与需求的两大利益主体,二者存在利益博弈关系。以水权为基础,在市场机制影响下,采用演化博弈方法,分析水源区和受水区两大利益主体的策略空间,建立大型调水工程水源区-受水区在市场机制作用下的演化博弈模型,确定利益主体在水源区环境保护中的行为决策关系,认为保障调水工程水源地水质的关键因素为水源区实施保护能否提高其综合社会经济效益,水源区要求的生态补偿形式和程度是否超过了受水区自身既得利益;根据演化博弈结果得出(保护,补偿)实现工程综合效益可持续的唯一决策方案,由此提出明确划分水权、加强生态补偿费用核算、加大生态补偿保障力度和补偿方式多元化等建议,以促进(保护,补偿)策略稳步实现。