A New Meta-Heuristic Algorithm for Optimization Based on Variance Reduction of Gaussian Distribution

Majlesi Journal of Electrical Engineering

مقاله 7، دوره 10، شماره 4، اسفند 2016   

نوع مقاله: Review Article

نویسندگان

Ali Namadchian؛ Mehdi Ramezani؛ Navid Razmjooy^*

University of Tafresh, Tafresh, Iran

چکیده

Meta-heuristic methods are global optimization algorithms which are widely used in the engineering issues, nowadays. In this paper, a new stochastic search for optimization is presented using variable variance Gaussian distribution sampling. The main idea in searching for algorithm is to regenerate new samples around each solution with a Guassian distribution. Numerical simulations have revealed that the new presented algorithm outperformed some evolutionary algorithms.

کلیدواژه‌ها

Optimization؛ en؛ Gaussian distribution؛ Covariance matrix؛ Stochastic search؛ Variance reduction؛ Probability Density Function (PDF؛ hereafter)

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