A Multi-Verse Optimizer with Levy Flights for Numerical Optimization and Its Application in Test Scheduling for Network-on-Chip.

A Multi-Verse Optimizer with Levy Flights for Numerical Optimization and Its Application in Test Scheduling for Network-on-Chip.
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一种用于数值优化的Levy飞行多维优化器及其在片上网络测试调度中的应用

DOI:
10.1371/journal.pone.0167341
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发表时间:
2016
期刊:
影响因子:
3.7
通讯作者:
Xu C
Xu C
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Hu C;Li Z;Zhou T;Zhu A;Xu C

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提出了一种新的元启发式算法--Levy航班多向优化算法(LFMVO),该算法将Levy航班引入到多向优化算法(MVO)中,用于求解数值和工程优化问题。最初的MVO很容易陷入停滞,当虫洞随机地重新跨越在迭代过程中获得的最好宇宙周围的一些宇宙(解)时。由于Levy飞行在探索未知的大规模搜索空间方面具有优势,它们被整合到之前的最佳宇宙中,以迫使MVO走出停滞。我们在三组23个著名的基准测试函数和一个片上网络测试调度的NP完全问题上测试了该方法。实验结果表明,LFMVO在解的质量和收敛速度上都比同类算法更具竞争力。
We propose a new meta-heuristic algorithm named Levy flights multi-verse optimizer (LFMVO), which incorporates Levy flights into multi-verse optimizer (MVO) algorithm to solve numerical and engineering optimization problems. The Original MVO easily falls into stagnation when wormholes stochastically re-span a number of universes (solutions) around the best universe achieved over the course of iterations. Since Levy flights are superior in exploring unknown, large-scale search space, they are integrated into the previous best universe to force MVO out of stagnation. We test this method on three sets of 23 well-known benchmark test functions and an NP complete problem of test scheduling for Network-on-Chip (NoC). Experimental results prove that the proposed LFMVO is more competitive than its peers in both the quality of the resulting solutions and convergence speed.
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