基于粒子群算法的三种新型并行模型的比较研究

Q3 Mathematics International Journal for Simulation and Multidisciplinary Design Optimization Pub Date : 2020-12-01 DOI:10.1051/smdo/2019022

M. Zemzami, Norelislam El Hami, M. Itmi, N. Hmina

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引用次数: 4

摘要

元启发式粒子群算法存在收敛过早、运行时间长等局限性，尤其是在复杂的优化问题上。本文在结合并行性和邻域这两个概念的基础上，对基于PSO算法的三个并行模型进行了描述，并根据三种不同的方法进行了设计，以避免PSO算法存在的两个缺点。第三个模型SPM（Spherical neighborhood Parallel model）是为了改进两个并行NPM（neighborhood并行模型）和MPM（Multi-PSO并行模型）模型的结果而设计的。实验结果表明，SPM模型在计算时间和求解质量方面都比NPM和MPM模型好得多。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A comparative study of three new parallel models based on the PSO algorithm

Meta-heuristic PSO has limits, such as premature convergence and high running time, especially for complex optimization problems. In this paper, a description of three parallel models based on the PSO algorithm is developed, on the basis of combining two concepts: parallelism and neighborhood, which are designed according to three different approaches in order to avoid the two disadvantages of the PSO algorithm. The third model, SPM (Spherical-neighborhood Parallel Model), is designed to improve the obtained results from the two parallel NPM (Neighborhood Parallel Model) and MPM (Multi-PSO Parallel Model) models. The experimental results presented in this paper show that SPM model performed much better than both NPM and MPM models in terms of computing time and solution quality.

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来源期刊

International Journal for Simulation and Multidisciplinary Design Optimization Mathematics-Control and Optimization

CiteScore

2.00

自引率

0.00%

发文量

审稿时长

16 weeks

期刊介绍： The International Journal for Simulation and Multidisciplinary Design Optimization is a peer-reviewed journal covering all aspects related to the simulation and multidisciplinary design optimization. It is devoted to publish original work related to advanced design methodologies, theoretical approaches, contemporary computers and their applications to different fields such as engineering software/hardware developments, science, computing techniques, aerospace, automobile, aeronautic, business, management, manufacturing,... etc. Front-edge research topics related to topology optimization, composite material design, numerical simulation of manufacturing process, advanced optimization algorithms, industrial applications of optimization methods are highly suggested. The scope includes, but is not limited to original research contributions, reviews in the following topics: Parameter identification & Surface Response (all aspects of characterization and modeling of materials and structural behaviors, Artificial Neural Network, Parametric Programming, approximation methods,…etc.) Optimization Strategies (optimization methods that involve heuristic or Mathematics approaches, Control Theory, Linear & Nonlinear Programming, Stochastic Programming, Discrete & Dynamic Programming, Operational Research, Algorithms in Optimization based on nature behaviors,….etc.) Structural Optimization (sizing, shape and topology optimizations with or without external constraints for materials and structures) Dynamic and Vibration (cover modelling and simulation for dynamic and vibration analysis, shape and topology optimizations with or without external constraints for materials and structures) Industrial Applications (Applications Related to Optimization, Modelling for Engineering applications are very welcome. Authors should underline the technological, numerical or integration of the mentioned scopes.).