Nature–inspired metaheuristic algorithms to find near–OGR sequences

What is it about?

This paper proposes three approaches to find near–optimal Golomb ruler (OGR) sequences based on nature–inspired algorithms in a reasonable time. The OGRs found their application in channel–allocation method that allows suppression of the crosstalk due to four–wave mixing in optical wavelength division multiplexing systems. The simulation results conclude that the proposed nature–inspired metaheuristic optimization algorithms are superior to the existing conventional and nature–inspired algorithms to find near–OGRs in terms of ruler length, total optical channel bandwidth, computation time, and computational complexity.

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Why is it important?

Based on the simulation results, the performance of proposed different nature–inspired metaheuristic algorithms are being compared by using statistical tests. The statistical test results conclude the superiority of the proposed nature–inspired optimization algorithms.