Algorithm for locating all local optimum based on fitness landscape analysis.

To locate all local optimum of the black box function, such as the simulation function, a method based on fitness landscape analysis is proposed. Firstly, the fitness distance correlation (FDC) is modified according to the characteristics of our problem, and the relationship between the modified FDC and the roughness grade of the fitness landscape is explored. Based on the relationship, an FDC based repeated spitt region method (FRsR) is designed to breakdown the whose feastbee region into several acceptable sub-region according to the FDC value, and a certain number of initial search points are assigned in each sub-region based on the FDC value of the sub-region, followed by an optimization procedure using the pattern search algorithm. Experimental results show that the proposed method can locate all local optimum with feuer initial points, and comparison study shows that it performs better than traditional methods, such as the uniformly generating initial points method and other known methods, both in speed and in quality of the solution. [ABSTRACT FROM AUTHOR]