大规模优化问题的杂交磷虾群算法

Ivana Stromberger, N. Bačanin, M. Tuba
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引用次数: 4

摘要

本文将磷虾群算法与萤火虫算法相结合,应用于有界约束的大规模优化问题。我们在基准函数的标准集上测试了基本磷虾群算法和基本萤火虫算法。结果是可以接受的。然后,将萤火虫算法的搜索方程应用到原磷虾群算法实现中,将磷虾群算法与萤火虫算法进行杂交。我们在相同的不同维数的大规模数值基准上测试了混合算法的鲁棒性和有效性,以进行对比分析和衡量我们的方法的优化增强。测试结果表明,我们提出的混合算法在处理全局优化问题时几乎一致地改善了结果,并且具有很大的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hybridized krill herd algorithm for large-scale optimization problems
In this paper we applied the krill herd algorithm hybridized with the firefly algorithm to bound-constrained large-scale optimization problems. We tested basic krill herd algorithm and basic firefly algorithm on the standard set of benchmark functions. The results were acceptable. Then, we hybridized the krill herd algorithm with the firefly algorithm by applying firefly algorithm's search equation to the original krill herd algorithm implementation. We tested the robustness and effectiveness of our hybridized algorithm on the same large-scale numerical benchmarks with different dimensionality in order to make comparative analysis and to measure optimization enhancements of our approach. Testing results proved that our proposed hybridized implementation improved results almost uniformly and that it has significant potential when dealing with global optimization problems.
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