ABSTRACT

This paper empirically compares the performance and scalability of Differential Evolution (DE) and Dynamic Differential Evolution (DDE) variants for solving high dimensional unconstrained global optimization functions. Four functions with different modality and decomposability viz unimodal separable, unimodal nonseparable, multimodal separable and multimodal nonseparable were chosen. Fourteen variants of DE and DDE were implemented and tested on these four benchmark functions, for the dimensions of 30,100, 500 and 1000. The performance of the variants are well compared by their mean objective function value (MOV), probability of convergence (Pc) and the success performance (SP). The analysis, done based on the results obtained for 100 runs for each variantfunction- dimension combination, identifies the competitiveness and the scalability of the variants.