Golomb Ruler Sequence Generation and Optimization using Modified Firefly Algorithm

International Journal of Electronics and Communication Engineering

© 2014 by SSRG - IJECE Journal

Volume 1 Issue 5

Year of Publication : 2014

Authors : Yogita Wadhwa , Parvinder Kaur and Baljeet Kaur

10.14445/23488549/IJECE-V1I5P101

How to Cite?

Yogita Wadhwa , Parvinder Kaur and Baljeet Kaur, "Golomb Ruler Sequence Generation and Optimization using Modified Firefly Algorithm," SSRG International Journal of Electronics and Communication Engineering, vol. 1,  no. 5, pp. 1-8, 2014. Crossref, https://doi.org/10.14445/23488549/IJECE-V1I5P101

Abstract:

Nature-inspired algorithms are among the most powerful algorithms for optimization problems. This paper intends to provide a detailed description of a Modified Firefly Algorithm (FA) Approach for Golomb Ruler Sequence Generation and optimization that allows suppression of the four wave mixing (FWM) crosstalk while maintaining channel bandwidth. We will compare the proposed modified firefly algorithm with other hard computing and soft computing algorithms such as Extended Quadratic Congruence (EQC), Search Algorithm (SA), Genetic Algorithm (GA), Biogeography Based Optimization (BBO), Firefly Algorithm (FA). Simulations results indicate that the proposed modified firefly algorithm is superior to existing hard computing and soft computing algorithms in terms of computational complexity

Keywords:

Four wave Mixing (FWM), Optimal Golomb Ruler (OGR), Firefly Algorithm (FA), Modified Firefly Algorithm (MFA)

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