Approximate probabilistic optimization using exact-capacity-approximate-response-distribution (ECARD)

Probabilistic structural design deals with uncertainties in response (e.g. stresses) and capacity (e.g. failure stresses). The calculation of the structural response is typically expensive (e.g., finite element simulations), while the capacity is usually available from tests. Furthermore, the random variables that influence response and capacity are often disjoint. In previous work we have shown that this disjoint property can be used to reduce the cost of obtaining the probability of failure via Monte Carlo simulations. In this paper we propose to use this property for an approximate probabilistic optimization based on exact capacity and approximate response distributions (ECARD). In Approximate Probabilistic Optimization Using ECARD, the change in response distribution is approximated as the structure is re-designed while the capacity distribution is kept exact, thus significantly reducing the number of expensive response simulations. ECARD may be viewed as an extension of SORA (Sequential Optimization and Reliability Assessment), which proceeds with deterministic optimization iterations. In contrast, ECARD has probabilistic optimization iterations, but in each iteration, the response distribution is approximated so as not to require additional response calculations. The use of inexpensive probabilistic optimization allows easy incorporation of system reliability constraints and optimal allocation of risk between failure modes. The method is demonstrated using a beam problem and a ten-bar truss problem. The former allocates risk between two different failure modes, while the latter allocates risk between members. It is shown that ECARD provides most of the improvement from risk re-allocation that can be obtained from full probabilistic optimization.     

解决矩阵链相乘处理器调度问题的一种新算法

本文介绍了矩阵链相乘处理器分配问题和离散处理器分配算法,描述了Lee Heejo等人提出的解决MCSP的处理器分配算法,提出了一种解决MCSP的时间复杂度更低的算法,使处理器能尽量被充分利用,并对三种分配算法进行了比较分析.     

基于效用公平的多用户下行OFDM系统机会调度

基于对单信道系统中效用公平机会调度的研究,提出了一种多用户下行OFDM多载波系统中的调度方案.该方案充分利用信道的时变和频率选择特性,由参数更新和调度决策两个模块组成:参数更新模块根据调度结果更新控制参数;调度决策模块根据所有用户的信道信息和参数更新模块输出的公平性控制参数决定该时隙每个用户使用哪些子载波.仿真结果表明,参数选取合适时,所提的简单调度方案能够在保证效用公平性的前提下,达到比复杂的Max-Min子裁波分配算法更好的系统性能.     

平流层通信平台MAC层的调度方案建模及仿真

平流层升空平台能够满足可提供战时服务、能快速部署,适用于区域性覆盖.为满足平台支持的多用户、多优先权、综合业务的接入策略并解决资源动态分配问题.提出了一种可以满足平台MAC层的服务质量(QoS)和动态带宽分配的调度架构,架构包括移动中心站(MCS)对移动站(MS)的带宽分配和移动站内上行业务的二级带宽调度架构,并根据不同业务需求采用不同的调度算法.仿真结果表明:调度方案能很好的满足所有类型业务的服务质量需求.并提供了较好的公平性,保证了架构的可行性.     

多类型热电机组群实时负荷动态分配方法

在运行灵活性提升背景下,考虑热电厂内不同类型热电机组的可行运行区间及其相关辅机运行动态安全边界,以实现热电厂整体效益最大为目标,提出一种多类型热电机组群实时负荷动态分配方法。该方法计及热电厂的售电收益、运行成本、辅助调峰市场收益、负荷跟踪惩罚,并通过设置机组出力最小调整量降低各机组出力调整频次。基于东北地区某热电厂实际数据的算例结果验证了所提方法的有效性和优越性。     

一种基于粒子群算法的DC-NOMA系统遍历容量优化方案

为提升设备到设备（Device-to-Device,D2D）辅助的协作非正交多址接入（Non-orthogonal Multiple Access,NOMA）中继系统的性能,以最大化系统遍历容量为目标建立优化模型,利用粒子群优化（Particle Swarm Optimization,PSO）算法设计最优功率分配策略,求出每个用户的最佳功率分配因子,从而得到系统遍历容量的最优值。仿真结果表明,所提出的基于PSO的功率分配方案不仅能提高系统容量,还可以降低用户的中断概率。     

民航空地通信中的多链路数据分配算法

针对民航空地通信数据丢失率高、吞吐量低问题,提出了一种基于丢包感知负载均衡(Packet Loss-Aware Load Balancing)的分配算法。在空地多链路通信中,每条链路的数据损失率随着链路状态与传输环境等情况实时变化。该算法通过控制每次空地通信中数据流的分割比率,动态分配给每条链路不同大小的数据流,使每条链路的传输损失率趋于相近,提高了空地通信系统吞吐量并减少了数据传输损失,以应对空地通信中丢包率高与吞吐量低等问题。仿真结果表明,所提算法在数据传输损失率和吞吐量上都优于现有的多链路子流分配算法。     

不确定信息下的评估指标权重配置方法

为了解决在数据不确定条件下极大熵权重配置模型找寻最优权重的问题,引入云模型将具有随机性和模糊性的数据转换为定性的数字特征。以此为基础在逼近理想解排序方法架构下定义了正负理想解,基于改进的欧氏距离设计了正负向距离,提出了多评估对象相对能力量化模型,并在极大熵准则下构建了新的权重配置模型,使得评估对象相对能力大小排序的专家知识得到充分运用。通过分析采用了模拟退火算法实现最优指标权重的搜寻,解决了原先算法模型不能应用于非凸优化情形的问题,进而给出科学合理的权重配置方案。仿真实例表明,在多次迭代后找寻到最优权重熵为1.377 7,满足要求,证明了所提算法的有效性。     

面向新型电力系统的变速抽蓄电站调频策略研究

针对变速抽蓄机组调频能力的高效利用问题,提出一种考虑混合抽蓄调频容量的协同调频策略研究。首先,以变分模态分解的调频信号高、低频分量作为混合抽蓄的初始调频参考;其次,利用2种抽蓄机组调频容量的差异对混合抽蓄的调频功率进行修正;最后,依据变速抽蓄机组转差率与调频容量关系,分配变速抽蓄机组之间的调频功率,实现混合抽蓄的有序调频。仿真结果表明了所提的变速抽蓄电站调频可以有效提高抽蓄电厂的调频响应速度。     

Difficulty and complexity definitions for assembly task allocation and assignment in human–robot collaborations: A review

This paper presents a literature review on the different aspects of task allocation and assignment problems in human–robot collaboration (HRC) tasks in industrial assembly environments. In future advanced industrial environments, robots and humans are expected to share the same workspace and collaborate to efficiently achieve shared goals. Difficulty- and complexity-aware HRC assembly is necessary for human-centric manufacturing, which is a goal of Industry 5.0. Therefore, the objective of this study is to clarify the definitions of difficulty and complexity used to encourage effective collaboration between humans and robots to leverage the adaptability of humans and the autonomy of robots. To achieve this goal, a systematic review of the following relevant databases for computer science was performed: IEEE Xplore, ScienceDirect, SpringerLink, ACM Digital Library, and ASME Digital Collection. The results extracted from 74 peer-reviewed research articles published until July 2022 were summarized and categorized into four taxonomies for 145 difficulty and complexity definitions from the perspectives of (1) definition-use objectives, (2) evaluation objectives, (3) evaluation factors, and (4) evaluation variables. Next, existing definitions were primarily classified according to the following two criteria to identify potential future studies on the formulation of new definitions for human-centric manufacturing: (1) agent specificity and (2) common aspects in manual and robotic assemblies.