Two-Phase Shuffled Frog-Leaping Algorithm

被引：0

作者：

Naruka, Bhagyashri ^{[1
]}

Sharma, Tarun K. ^{[1
]}

Pant, Millie ^{[2
]}

Rajpurohit, Jitendra ^{[1
]}

Sharma, Shweta ^{[1
]}

机构：

[1] Amity Univ Rajasthan, Jaipur, Rajasthan, India

[2] IIT Roorkee, Roorkee, Uttar Pradesh, India

来源：

2014 3RD INTERNATIONAL CONFERENCE ON RELIABILITY, INFOCOM TECHNOLOGIES AND OPTIMIZATION (ICRITO) (TRENDS AND FUTURE DIRECTIONS) | 2014年

关键词：

shuffled frog-leaping algorithm; optimization; convergence; engineering design problems; OPTIMIZATION; COLONY;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Shuffled frog-leaping algorithm (SFLA) is a recent addition to the stochastic search methods that mimics the social and natural behaviour of species. The basic idea behind modelling of such algorithms is to achieve comparatively better solutions to the multifaceted optimization problems that are not easy to solve using traditional or deterministic mathematical techniques. SFLA combines the advantages of particle swarm optimization (PSO) and genetic algorithm (GA). In this study to improve the convergence speed, two modifications have been proposed firstly, initial population is generated using opposition based learning and secondly search process of SFLA is improved using scaling factor. The proposed algorithm is named as TwoPhase SFLA. The impact of the proposal is illustrated on four structural engineering design problems.

引用

页数：5

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