磷虾群算法混合方法的比较

Ai Nurhayati, Aditya Gautama Darmoyono
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引用次数: 0

摘要

磷虾群算法是由海洋中磷虾群的运动来驱动的。它是一种寻找全局最优值的启发式搜索方法。本文将混合磷虾群量子粒子群优化算法(KHQPSO)、生物地理磷虾群算法(BKH)和和谐搜索磷虾群算法(HSKH)作为磷虾群算法的组合进行了比较。研究结果表明,BKH算法在求解标准测试函数方面具有比KHQPSO和HSKH算法更好的性能。
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A Comparison of Hybrid Methods of the Krill Herd Algorithm
Krill herd algorithm is motivated by the movement of krill herd in the sea. It is a heuristic search method for finding global optimum value. This paper presents a comparison between a mix Krill Herd Quantum Particle Swarm Optimization (KHQPSO) algorithm, a Biogeography Krill Herd (BKH) algorithm and Harmony Search Krill Herd (HSKH) algorithm as a combination of Krill Herd algorithm. The results of the study prove that BKH has better performance than KHQPSO and HSKH algorithm for solving standard test functions.
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