Title: A multi-group dragonfly algorithm for application in wireless sensor network deployment problem

Authors: Xiaopeng Wang; Shu-Chuan Chu; Han-Chieh Chao; Jeng-Shyang Pan

Addresses: College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China ' College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China ' Department of Electrical Engineering, National Dong Hwa University, Hualien 97047, Taiwan ' College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China; Department of Information Management, Chaoyang University of Technology, Taichung 413310, Taiwan

Abstract: Metaheuristic algorithm is a popular research field. In recent years, a host of optimisers have been presented. Dragonfly algorithm (DA) mimicking the behaviour of a dragonfly performs markedly competitive to some optimisation problems. However, the DA sometimes does not perform well when encountering some complicated problems, easily falls into the local optimum, and premature convergence. To overcome the deficiencies of the canonical DA, this paper presents an enhanced version of DA, namely the multi-group dragonfly algorithm (MDA). The proposed MDA with three communication strategies applies effectively the multi-group trick to improve the diversity of the population. To verify the performance of the proposed MDA, it is evaluated by different benchmarks including unimodal functions, multimodal functions, hybrid, and composed functions. The experimental data confirm that the MDA performs better than the DA. Besides, the MDA is also applied in the wireless sensor network deployment problem, the simulation results appear that the MDA can obtain a more ideal sensor node distribution.

Keywords: metaheuristic algorithm; multi-group dragonfly algorithm; dragonfly algorithm; wireless sensor network deployment problem.

DOI: 10.1504/IJAHUC.2021.117333

International Journal of Ad Hoc and Ubiquitous Computing, 2021 Vol.37 No.4, pp.227 - 239

Received: 16 Nov 2020
Accepted: 31 Mar 2021
Published online: 31 Aug 2021 *

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