@inproceedings{50ae66dcf5a24c7a88cf44663158b458,
title = "A novel hybrid GWO-FPA algorithm for optimization applications",
abstract = "The recent trend of research is to hybridize two or several numbers of variants to find out the better quality of solution in practical optimization applications. In this paper, a new approach hybrid Grey Wolf Optimizer (GWO)-Flower Pollination Algorithm (FPA) is proposed based on the combination of exploitation phase in GWO and exploration stage in FPA. The hybrid proposed GWOFPA improves movement directions and speed of the grey wolves in updating positions of FPA. The simulation uses six benchmark tests for evaluating the performance of the proposed method. Compared other metaheuristics such as Particle Swarm Optimization (PSO), FPA, and GWO, the simulation results demonstrate that the proposed approach offers the better performance in solving optimization problems with or without unknown search areas.",
keywords = "Flower Pollination Algorithm, Grey Wolf Optimizer, Hybrid GWO-FPA algorithm, Optimization",
author = "Pan, {Jeng Shyang} and Dao, {Thi Kien} and Chu, {Shu Chuan} and Nguyen, {Trong The}",
year = "2018",
doi = "10.1007/978-3-319-70730-3_33",
language = "English",
isbn = "9783319707297",
series = "Smart Innovation, Systems and Technologies",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "274--281",
editor = "Jeng-Shyang Pan and Tsu-Yang Wu and Yong Zhao and Jain, {Lakhmi C.}",
booktitle = "Advances in Smart Vehicular Technology, Transportation, Communication and Applications - Proceedings of the 1st International Conference on Smart Vehicular Technology, Transportation, Communication and Applications",
note = "1st International Conference on Smart Vehicular Technology, Transportation, Communication and Applications, VTCA 2017 ; Conference date: 06-11-2017 Through 08-11-2017",
}