Practical methods of optimization; (2nd ed.)
Practical methods of optimization; (2nd ed.)
The globally convexized filled functions for global optimization
Applied Mathematics and Computation
Evolutionary computation: toward a new philosophy of machine intelligence
Evolutionary computation: toward a new philosophy of machine intelligence
SPT: a stochastic tunneling algorithm for global optimization
Journal of Global Optimization
New Classes of Globally Convexized Filled Functions for Global Optimization
Journal of Global Optimization
Multiobjective programming using uniform design and genetic algorithm
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Evolutionary programming made faster
IEEE Transactions on Evolutionary Computation
An orthogonal genetic algorithm with quantization for globalnumerical optimization
IEEE Transactions on Evolutionary Computation
Evolutionary programming using mutations based on the Levy probability distribution
IEEE Transactions on Evolutionary Computation
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In this paper, a novel technique called Fourier smoothing technique, which can be used to improve any global optimization algorithm, is presented. This technique uses a properly truncated Fourier series as the smoothing function to approximate the objective function. This smoothing function can maintain the overall shape or basic shape of the objective function but eliminate its finer details. Thus it can eliminate many local minima but preserve the global minima, and make the search of optimal solution more easier and faster. To demonstrate efficiency of this technique, we integrate this technique into a simple optimization algorithm: Powell direct method. The simulation results indicate this smoothing technique can improve the Powell direct method greatly.