There is a remarkable performance of differential evolution (DE) algorithm on continuous space problem. Mutation plays a very vital role in success of DE but in traditional DE all the vectors are selected in random manner. Sometimes, it gives a random exploration in search space. Here, the distance-based analysis for mutation vector selection is carried out and distance-based criteria for base vector (reference point) selection have proposed. Experimentation is conducted on eight standard uni-model and multi-model functions. Later, the results have compared with standard DE and other variant of DE. Experiments show that the proposed strategy has a very steady and stable exploration of search space.
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