Converging Marriage in Honey-Bees Optimization and Application to Stochastic Dynamic Programming

In this paper, we first refine a recently proposed metaheuristic called “Marriage in Honey-Bees Optimization” (MBO) for solving combinatorial optimization problems with some modifications to formally show that MBO converges to the global optimum value. We then adapt MBO into an algorithm called “Honey-Bees Policy Iteration” (HBPI) for solving infinite horizon-discounted cost stochastic dynamic programming problems and show that HBPI also converges to the optimal value.     

Investigation of the equality constraint effect on the reduction of the rotational ambiguity in three-component system using a novel grid search method

The obtained results by soft modeling multivariate curve resolution methods often are not unique and are questionable because of rotational ambiguity. It means a range of feasible solutions equally fit experimental data and fulfill the constraints. Regarding to chemometric literature, a survey of useful constraints for the reduction of the rotational ambiguity is a big challenge for chemometrician. It is worth to study the effects of applying constraints on the reduction of rotational ambiguity, since it can help us to choose the useful constraints in order to impose in multivariate curve resolution methods for analyzing data sets. In this work, we have investigated the effect of equality constraint on decreasing of the rotational ambiguity. For calculation of all feasible solutions corresponding with known spectrum, a novel systematic grid search method based on Species-based Particle Swarm Optimization is proposed in a three-component system.     

Sintered silver finite element modelling and reliability based design optimisation in power electronic module

This paper discusses the design for reliability of a sintered silver structure in a power electronic module based on the computational approach that composed of high fidelity analysis, reduced order modelling, numerical risk analysis, and optimisation. The methodology was demonstrated on sintered silver interconnect sandwiched between silicon carbide chip and copper substrate in a power electronic module. In particular, sintered silver reliability due to thermal fatigue material degradation is one of the main concerns. Thermo-mechanical behaviour of the power module sintered silver joint structure is simulated by finite element analysis for cyclic temperature loading profile in order to capture the strain distribution. The discussion was on methods for approximate reduced order modelling based on interpolation techniques using Kriging and radial basis functions. The reduced order modelling approach uses prediction data for the thermo-mechanical behaviour. The fatigue lifetime of the sintered silver interconnect and the warpage of the interconnect layer was particular interest in this study. The reduced order models were used for the analysis of the effect of design uncertainties on the reliability of the sintered silver layer. To assess the effect of uncertain design data, a method for estimating the variation of reliability related metrics namely Latin Hypercube sampling was utilised. The product capability indices are evaluated from the distributions fitted to the histogram resulting from Latin Hypercube sampling technique. A reliability based design optimisation was demonstrated using Particle Swarm Optimisation algorithm for constraint optimisation task consists of optimising two different characteristic performance metrics such as the thermo-mechanical plastic strain accumulation per cycle on the sintered layer and the thermally induced warpage.     

基于改进型粒子群算法的阵列天线综合

粒子群优化(PSO)算法是一种通过粒子之间的合作与竞争来实现复杂多维空间的最优区域搜索的优化算法。本文中改进型PSO算法(NPSO),通过增加积分控制项改善了PSO算法全局搜索能力,并将该方法应用于多元环形阵列天线方向图的综合,实现了阵列方向图与预先给定的目标方向图的高度逼近。最后通过数值实例说明这种NPSO方法的有效性。     

WDM光纤通信系统中PMD自动补偿的研究

文章提出采用粒子群优化算法,提取信号的偏振度(DOP)作为反馈信号来补偿多信道光纤通信系统中的偏振模色散(PMD).作为例子,对两信道的波分复用(WDM)系统中的PMD进行了自动补偿,并进行了数值模拟,得到了两个信道补偿前后的DOP以及眼图变化情况.模拟结果表明这种算法对补偿多个信道的PMD是有效的.     

Data and modeling of negative ion transport in gases of interest for production of integrated circuits and nanotechnologies

We review techniques to prepare, evaluate and apply sets of cross section and transport data for negative ions that are required for the modeling of collisional non-equilibrium plasmas used for processing of microelectronic circuits. We collect and discuss the transport coefficients and cross section sets.We have compiled data for negative ions in CF₄ and CF₄-related negative ions in rare gases. In addition, we consider data for F⁻ and CF₃⁻ in rare gases. Furthermore, we analyze the cross sections of halogen negative ions in rare gases and other molecules. This is followed by the data for SF₆ related ions in SF₆ and in rare gases. The cross section for scattering of O⁻ in O₂ has been derived from the transport data and used to make calculations of the transport properties. Finally we give a brief discussion of the availability of the data for H⁻ ions in H₂. We have derived cross sections in several cases but the basic aim is to show the basic features of transport coefficients. In particular we discuss the need to represent properly some details such as the non-conservative nature of transport coefficients and the anisotropy of diffusion. Application of approximate theories and representations of cross sections are also discussed.     

Inverse transient radiation analysis in one-dimensional non-homogeneous participating slabs using particle swarm optimization algorithms

Particle Swarm Optimization (PSO) algorithms, including standard PSO, Stochastic PSO, and Multi-Phase PSO, are applied to solve the time-domain inverse transient radiation problems in the present research. Time-resolved transmittance and reflectance signals of four different measuring models serve as the measurement data, which estimate absorption, scattering coefficients, and geometric position within one-dimensional non-homogeneous media by inverse simulation. To check retrieval performances and accuracies of PSO-based approaches, four different inverse transient radiation cases are investigated to deal with one homogeneous layer, two-layer, three-layer, and continuous non-homogenous media. The influences of different searching ranges, swarm sizes, and maximum fly velocities on the fitness function of PSO are discussed. Meanwhile, the effects of measurement errors on the reconstruction accuracy are also investigated. All the results confirm that radiative parameters could be estimated accurately with measurement noise using PSO-based approaches.     

An interactive dynamic approach based on hybrid swarm optimization for solving multiobjective programming problem with fuzzy parameters

Real engineering design problems are generally characterized by the presence of many often conflicting and incommensurable objectives. Naturally, these objectives involve many parameters whose possible values may be assigned by the experts. The aim of this paper is to introduce a hybrid approach combining three optimization techniques, dynamic programming (DP), genetic algorithms and particle swarm optimization (PSO). Our approach integrates the merits of both DP and artificial optimization techniques and it has two characteristic features. Firstly, the proposed algorithm converts fuzzy multiobjective optimization problem to a sequence of a crisp nonlinear programming problems. Secondly, the proposed algorithm uses H-SOA for solving nonlinear programming problem. In which, any complex problem under certain structure can be solved and there is no need for the existence of some properties rather than traditional methods that need some features of the problem such as differentiability and continuity. Finally, with different degree of α we get different α-Pareto optimal solution of the problem. A numerical example is given to illustrate the results developed in this paper.     

QPSO与K-Medoids相结合的带障碍空间聚类新算法

分析了现有的带障碍约束空间聚类算法,针对基于PSO优化的带障碍约束的K-Me足,提出了QPSO与K-Medoids算法结合的带障碍空间聚类新算法(QKSCO).在带障碍约束的空间条件下,该算法依据蚁群格网障碍距离作为聚类依据,引入了QPSO的快速全局收敛的特性,使之与K-Medoids算法的局部收敛特性相得益彰.实验结...     

Leadership Hijacking in Docker Swarm and Its Consequences

With the advent of microservice-based software architectures, an increasing number of modern cloud environments and enterprises use operating system level virtualization, which is often referred to as container infrastructures. Docker Swarm is one of the most popular container orchestration infrastructures, providing high availability and fault tolerance. Occasionally, discovered container escape vulnerabilities allow adversaries to execute code on the host operating system and operate within the cloud infrastructure. We show that Docker Swarm is currently not secured against misbehaving manager nodes. This allows a high impact, high probability privilege escalation attack, which we refer to as leadership hijacking, the possibility of which is neglected by the current cloud security literature. Cloud lateral movement and defense evasion payloads allow an adversary to leverage the Docker Swarm functionality to control each and every host in the underlying cluster. We demonstrate an end-to-end attack, in which an adversary with access to an application running on the cluster achieves full control of the cluster. To reduce the probability of a successful high impact attack, container orchestration infrastructures must reduce the trust level of participating nodes and, in particular, incorporate adversary immune leader election algorithms.