Ali Namadchian - University of Tafresh, Tafresh, Iran
Mehdi Ramezani - University of Tafresh, Tafresh, Iran
Navid Razmjooy - University of Tafresh, Tafresh, Iran

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.

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