Title: A sine cosine mutation based differential evolution algorithm for solving node location problem

Authors: Chong Zhou; Liang Chen; Zhikun Chen; Xiangping Li; Guangming Dai

Addresses: School of Computer, China University of Geosciences, Wuhan 430074, China ' School of Computer, China University of Geosciences, Wuhan 430074, China ' School of Computer, China University of Geosciences, Wuhan 430074, China ' School of Computer, China University of Geosciences, Wuhan 430074, China ' School of Computer, China University of Geosciences, Wuhan 430074, China

Abstract: Differential Evolution (DE) algorithm is known in evolutionary computation. However, DE with DE/best/1 mutation has some drawbacks such as premature convergence and local optimum. To address these drawbacks, we improve the DE/best/1 mutation operator and propose a sine cosine mutation based differential evolution algorithm, named SCDE. In the proposed method, a new sine cosine mutation operator inspired by sine cosine algorithm (SCA) is adopted to balance exploration and exploitation. In the experimental simulation, the proposed algorithm is compared with three state-of-the-art algorithms on the well-known benchmark test functions. The results of test functions and performance metrics show that the proposed algorithm is able to avoid local optima and converge towards the global optimum. In addition, the proposed algorithm is used to solve sensor node location in wireless sensor network. Results show that our algorithm is effective.

Keywords: differential evolution algorithm; sine cosine algorithm; sine cosine mutation; local optimum; sensor node location.

DOI: 10.1504/IJWMC.2017.088531

International Journal of Wireless and Mobile Computing, 2017 Vol.13 No.3, pp.253 - 259

Received: 09 May 2017
Accepted: 13 Jun 2017

Published online: 04 Dec 2017 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article