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Canonical deterministic particle swarm optimization to sustain global search

机译:典型确定性粒子群优化算法可维持全局搜索

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Particle swarm optimization is very simple algorithm. However, the trajectory of each particle becomes pretty complicated because each particle is affected by the information of the other particles. In order to analyze the dynamics of the PSO rigorously, we propose the canonical deterministic PSO (CD-PSO). The CD-PSO is described by a canonical form, and the dynamics is characterized by the damping factor and the rotational angle. The dynamics of the CD-PSO can be analyzed theoretically, however, the solution search performance is worse than the conventional PSO. The reason why the performance of the CD-PSO is poor, is the rotation radius of the particle is decreased with the change of the best position. The small rotation radius contributes to the local search ability, but the global search ability is spoiled. Therefore, we propose a method to sustain the global search for the CD-PSO. The function is realized by maintaining the rotation radius. Applying the proposed method for the CD-PSO, the solution search performance improves that of the conventional CD-PSO.
机译:粒子群优化是非常简单的算法。但是,每个粒子的轨迹变得非常复杂,因为每个粒子都受到其他粒子信息的影响。为了严格分析PSO的动态性,我们提出了规范确定性PSO(CD-PSO)。 CD-PSO用规范形式描述,动态特性用阻尼系数和旋转角度来表征。 CD-PSO的动力学可以从理论上进行分析,但是,解决方案的搜索性能比常规PSO差。 CD-PSO性能差的原因是,随着最佳位置的变化,颗粒的旋转半径减小。小的旋转半径有助于局部搜索能力,但是整体搜索能力却被破坏了。因此,我们提出了一种方法来维持CD-PSO的全局搜索。该功能是通过保持旋转半径来实现的。将所提出的方法应用于CD-PSO,解决方案的搜索性能提高了传统CD-PSO的搜索性能。

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