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Nature–inspired metaheuristic algorithms to find near–OGR sequences for WDM channel allocation and their performance comparison

Shonak Bansal, Neena Gupta, Arun Kumar Singh (2017)

Open Mathematics

Nowadays, nature–inspired metaheuristic algorithms are most powerful optimizing algorithms for solving the NP–complete problems. This paper proposes three approaches to find near–optimal Golomb ruler sequences based on nature–inspired algorithms in a reasonable time. The optimal Golomb ruler (OGR) sequences 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...

New technique for solving univariate global optimization

Djamel Aaid, Amel Noui, Mohand Ouanes (2017)

Archivum Mathematicum

In this paper, a new global optimization method is proposed for an optimization problem with twice differentiable objective function a single variable with box constraint. The method employs a difference of linear interpolant of the objective and a concave function, where the former is a continuous piecewise convex quadratic function underestimator. The main objectives of this research are to determine the value of the lower bound that does not need an iterative local optimizer. The proposed method...

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