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

被引:33
|
作者
Hu, Cong [1 ,2 ]
Li, Zhi [1 ,3 ]
Zhou, Tian [2 ]
Zhu, Aijun [2 ]
Xu, Chuanpei [2 ]
机构
[1] Xidian Univ, Sch Mechanoelect Engn, Xian, Shaanxi, Peoples R China
[2] Guilin Univ Elect Technol, Sch Elect Engn & Automat, Guilin, Guangxi, Peoples R China
[3] Guilin Univ Aerosp Technol, Guilin, Guangxi, Peoples R China
来源
PLOS ONE | 2016年 / 11卷 / 12期
基金
中国国家自然科学基金;
关键词
GLOBAL OPTIMIZATION; PARTICLE SWARM; TEST ACCESS; ALGORITHM; SEARCH;
D O I
10.1371/journal.pone.0167341
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页数:22
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