This paper describes a method for searching of global minima in design optimization problems. The method is applicable to any general nonlinear function. It is based on utilizing sensitive fractal areas to locate all of the solutions along one direction in a variable space. The search begins from an arbitrary chosen point in the variable space and descends towards a better design along a randomly chosen direction. Descent depends on finding points that belong to a fractal set which can be used to locate all of the solutions along that direction. The process is repeated until optimal design is obtained. To examine the behavior of the algorithm appropriate examples were selected and results discussed. [S1050-0472(00)00703-0]

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