Archimedes Optimization Algorithm Combining Differential Evolution and Multi Strategy
In view of the shortcomings of the Archimedes optimization algorithm,such as prematurity and slow convergence,this paper proposes an Archimedes optimization algorithm which combines differential evolution and multi-strategy.Firstly,two chaotic maps were ran-domly selected to initialize the population through location parameters to enhance the diver-sity of the population.Secondly,the dynamic boundary strategy of cosine control factor is used to improve the density factor to balance the global exploration and local development ability of the algorithm.Then,the differential evolution algorithm is integrated to narrow the range of the optimal position,so as to achieve the purpose of getting closer to the optimal po-sition quickly.Finally,10 benchmark test functions were selected for simulation experiments,and the experimental results were tested by Wilcoxon rank sum test.The results show that the proposed algorithm performs better than the comparison algorithm.
Archimedes optimization algorithmdifferential evolution algorithmchaotic mappingcosine control factordynamic boundary
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