A modified particle swarm optimization with multiple subpopulations for multimodal function optimization problems

In this paper, a modified particle swarm optimization (PSO) algorithm is developed for solving multimodal function optimization problems. The difference between the proposed method and the general PSO is to split up the original single population into several subpopulations according to the order of particles. The best particle within each subpopulation is recorded and then applied into the velocity updating formula to replace the original global best particle in the whole population. To update all particles in each subpopulation, the modified velocity formula is utilized. Based on the idea of multiple subpopulations, for the multimodal function optimization the several optima including the global and local solutions may probably be found by these best particles separately. To show the efficiency of the proposed method, two kinds of function optimizations are provided, including a single modal function optimization and a complex multimodal function optimization. Simulation results will demonstrate the convergence behavior of particles by the number of iterations, and the global and local system solutions are solved by these best particles of subpopulations.     

A semicontinuous approach for heterogeneous azeotropic distillation processes

The separation of azeotropes has substantial energy and investment costs, and the available methods require high capital costs for reconstruction of process plants. As an alternative, a semicontinuous configuration that utilizes an existing plant with minor modifications has been explored. In this paper, a semicontinuous, heterogeneous azeotropic distillation process is proposed and acetic acid dehydration process is used as a case study. To carry out the simulation work, Aspen HYSYS^® simulation software is used along with MATLAB^® and an interface program to handle the mode-transition of the semicontinuous process. Sensitivity analyses on operating parameters are performed to identify the process limits. Comparisons are made to conventional heterogeneous azeotropic distillation, and dividing-wall distillation column on the annual cost. The results proved that the semicontinuous system is the best setup in terms of total annual costs and energy requirements.     

Reliability of complex chemical engineering processes

This paper presents a stochastic performance modelling approach that can be used to optimise design and operational reliability of complex chemical engineering processes. The framework can be applied to processes comprising multiple units, including the cases where closed form process performance functions are unavailable or difficult to derive from first principles, which is often the case in practice. An interface that facilitates automated two-way communication between Matlab^® and process simulation environment is used to generate large process responses. The resulting constrained optimisation problem is solved using both Monte Carlo Simulation (MCS) and First Order Reliability Method (FORM); providing a wide range of stochastic process performance measures. Adding such capabilities to traditional deterministic process simulators provides a more informed basis for selecting optimum design factors; giving a simple way of enhancing overall process reliability and cost-efficiency. Two case study systems are considered to highlight the applicability and benefits of the approach.     

Synthesis and Characterization of Co Nanocomposite Based on Poly(benzimidazole-amide) Matrix and Their Behavior as Catalyst in Oxidation Reaction

2,6-Bis(5-amino-1H-benzimidazol-2-yl)pyridine was prepared and characterized by Fourier transform infrared spectroscopy, elemental analysis, ¹H-NMR, and ¹³C-NMR spectroscopic methods. Then a new poly(benzimidazole-amide) was synthesized by polymerization of the corresponding diamine and isophthalic acid. The obtained poly(benzimidazole-amide) exhibited good yield and high thermal stability. Due to the existence of benzimidazole moieties in polymer’s structure, it has the tendency to form complexes with metal ions. So, a new poly(benzimidazole-amide)/Co nanocomposite was prepared. Morphological studies revealed that metal nanoparticles were dispersed in the polymer matrix without any aggregation. poly(benzimidazole-amide)/Co nanocomposite was used as a catalyst in the oxidation of ethyl benzene to acetophenone with tert-butyl hydroperoxide.     

Hierarchical multi-reservoir optimization modeling for real-world complexity with application to the Three Gorges system

High dimensionality in real-world multi-reservoir systems greatly hinders the application and popularity of evolutionary algorithms, especially for systems with heterogeneous units. An efficient hierarchical optimization framework is presented for search space reduction, determining the best water distributions, not only between cascade reservoirs, but also among different types of hydropower units. The framework is applied to the Three Gorges Project (TGP) system and the results demonstrate that the difficulties of multi-reservoir optimization caused by high dimensionality can be effectively solved by the proposed hierarchical method. For the day studied, power output could be increased by 6.79 GWh using an optimal decision with the same amount of water actually used; while the same amount of power could be generated with 2.59 × 10⁷ m³ less water compared to the historical policy. The methodology proposed is general in that it can be used for other reservoir systems and other types of heterogeneous unit generators.     

Parallel chaos optimization algorithm with migration and merging operation

Chaos optimization algorithm (COA) utilizes the chaotic maps to generate the pseudo-random sequences mapped as the decision variables for global optimization applications. A kind of parallel chaos optimization algorithm (PCOA) has been proposed in our former studies to improve COA. The salient feature of PCOA lies in its pseudo-parallel mechanism. However, all individuals in the PCOA search independently without utilizing the fitness and diversity information of the population. In view of the limitation of PCOA, a novel PCOA with migration and merging operation (denoted as MMO-PCOA) is proposed in this paper. Specifically, parallel individuals are randomly selected to be conducted migration and merging operation with the so far parallel solutions. Both migration and merging operation exchange information within population and produce new candidate individuals, which are different from those generated by stochastic chaotic sequences. Consequently, a good balance between exploration and exploitation can be achieved in the MMO-PCOA. The impacts of different one-dimensional maps and parallel numbers on the MMO-PCOA are also discussed. Benchmark functions and parameter identification problems are used to test the performance of the MMO-PCOA. Simulation results, compared with other optimization algorithms, show the superiority of the proposed MMO-PCOA algorithm.     

Weighted Superposition Attraction (WSA): A swarm intelligence algorithm for optimization problems – Part 2: Constrained optimization

This paper is the second one of the two papers entitled “Weighted Superposition Attraction (WSA) Algorithm”, which is about the performance evaluation of the WSA algorithm in solving the constrained global optimization problems. For this purpose, the well-known mechanical design optimization problems, design of a tension/compression coil spring, design of a pressure vessel, design of a welded beam and design of a speed reducer, are selected as test problems. Since all these problems were formulated as constrained global optimization problems, WSA algorithm requires a constraint handling method for tackling them. For this purpose we have selected 6 formerly developed constraint handling methods for adapting into WSA algorithm and analyze the effect of the used constraint handling method on the performance of the WSA algorithm. In other words, we have the aim of producing concluding remarks over the performance and robustness of the WSA algorithm through a set of computational study in solving the constrained global optimization problems. Computational study indicates the robustness and the effectiveness of the WSA in terms of obtained results, reached level of convergence and the capability of coping with the problems of premature convergence, trapping in a local optima and stagnation.     

搅拌式风力致热装置启动性能研究

搭建搅拌式风力致热试验台,以自制的2种致热器为研究对象,使其分别在3个不同平均角加速度24.92、14.66、8.04 rad/s2下启动。通过动态扭矩测试仪和数据采集仪测试记录致热器启动阶段的相关数据。结果表明:致热器启动时所需扭矩与角加速度的一次方、转速、叶片半径的二次方成正比,同时得出这些因素之间的关系式;满负荷时,启动扭矩会出现一个峰值,且角加速度越大峰值越大,自然风必须提供峰值以上的扭矩,否则装置无法启动。     

基于词法特征的恶意域名快速检测算法

针对互联网中恶意域名攻击事件频发，现有域名检测方法实时性不强的问题，提出一种基于词法特征的恶意域名快速检测算法。该算法根据恶意域名的特点，首先将所有待测域名按照长度进行正则化处理后赋予权值；然后利用聚类算法将待测域名划分成多个小组，并利用改进的堆排序算法按照组内权值总和计算各域名小组优先级，根据优先级降序依次计算各域名小组中每一域名与黑名单上域名之间的编辑距离；最后依据编辑距离值快速判定恶意域名。算法运行结果表明，基于词法特征的恶意域名快速检测算法与单一使用域名语义和单一使用域名词法的恶意域名检测算法相比，准确率分别提高1.7%与2.5%，检测速率分别提高13.9%与6.8%，具有更高的准确率和实时性。     

Multiobjective PSO based adaption of neural network topology for pixel classification in satellite imagery

The proposed work involves the multiobjective PSO based adaption of optimal neural network topology for the classification of multispectral satellite images. It is per pixel supervised classification using spectral bands (original feature space). This paper also presents a thorough experimental analysis to investigate the behavior of neural network classifier for given problem. Based on 1050 number of experiments, we conclude that following two critical issues needs to be addressed: (1) selection of most discriminative spectral bands and (2) determination of optimal number of nodes in hidden layer. We propose new methodology based on multiobjective particle swarm optimization (MOPSO) technique to determine discriminative spectral bands and the number of hidden layer node simultaneously. The accuracy with neural network structure thus obtained is compared with that of traditional classifiers like MLC and Euclidean classifier. The performance of proposed classifier is evaluated quantitatively using Xie-Beni and β indexes. The result shows the superiority of the proposed method to the conventional one.