Študija samoprilagajanja krmilnih parametrov pri algoritmu DEMOwSA - Zamuda, Aleš (Elektrotehniški vestnik, 2008)
In this paper we present an experimental analysis showing that the self-adaptation of control parameters plays an important role in the multiobjective optimization process (refer to Figure I for notion of multiobjective optimality). Experimental results of a self-adaptive differential evolution algorithm are evaluated on the set of benchmark functions provided for the CEC 2007 Special session on Performance Assessment & Competition on Multi-objective Optimization Algorithms, as seen in Tables 2-7. Self-adaptation is proven to statistically outperform fixed parameters, using t-test on the empirical results in these tables. The values of control parameters are encoded in each individual (see Figure 2) and changed during the optimization process. They depend on the nature of the problem being solved, as can be seen in Table I and Figures 3 and 4 which show how using self-adaptation good control parameters are obtained to improve the search results.
Keywords: evolucijsko računanje; diferencialna evolucija; večkriterijska optimizacija; samoprilagajanje; evolucijski algoritmi