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引用次数: 0
摘要
政治优化算法是近年来学者提出的一种元启发式算法。它反映了较好的收敛速度以及在寻找最优解相关问题上的开发和探索能力。然而,对于全局最优,它仍有改进的空间。本文提出了一种混合政治算法(Hybrid Political Algorithm),该算法对探索过程和算法功能进行了平衡修改,通过使粒子在计算过程中更智能地移动,有效地提高了在进化计算大会数学问题和工程问题中寻找最优解的能力。从实验结果来看,利用本文提出的方法提高算法函数的性能也有助于避免陷入局部最优。此外,与其他算法相比,改进后的算法可以生成更准确的结果。
Hybrid Political Algorithm Approach for Engineering Optimization Problems
Political Optimizer is a metaheuristic algorithm proposed by scholars recently. It reflects good convergence speed as well as exploitation and exploration capabilities in problems relevant to finding optimal solutions. However, regarding the global optimum, it still has spaces to be improved. This study proposed a Hybrid Political Algorithm, which makes balanced modifications to the exploration process and algorithm functions to effectively improve searching for the optimal solutions in the mathematic problems of Congress on Evolutionary Computation and engineering problems by enabling the particles to move smarter in the computation process. Based on the experimental results, improving the performance of algorithm functions using the methods proposed in this study can also help avoid falling into the local optimum. In addition, compared to other algorithms, this improved algorithm can generate more accurate results.