Topographical Differential Evolution Using Pre-calculated Differentials

We present an algorithm for finding the global minimum of multimodal functions. The proposed algorithm is based on differential evolution (DE). Its distinguishing features are that it implements pre-calculated differentials and that it suitably utilizes topographical information on the objective function in deciding local search. These features are implemented in a periodic fashion. The algorithm has been tested on easy, moderately difficult test problems as well as on the difficult Lennard-Jones (LJ) potential function. Computational results using problems of dimensions upto 24 are reported. A robust computational behavior of the algorithm is shown.

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