a hybrid improved flock optimization algorithm (Powell-LCSO) is proposed to overcome the shortcomings of the traditional flock optimization algorithm (CSO) which is easy to fall into the local extremum and easy to premature convergence. Firstly
the improved algorithm uses Logistic chaotic map to initialize the population
which makes the population better distributed in the solution space. Secondly
the position of the hens in the flocks is improved. Finally
by comparing the Limit threshold to determine whether the algorithm is caught in the local extremum
and using the Powell search to local search for the global optimal individuals
it avoids the premature convergence of the algorithm and improves the accuracy of the algorithm. Its ability to jump out of the local best. Experiments show that the improved flock optimization algorithm has good accuracy and convergence efficiency.
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Sabat S L, Kumar K S, Udgata S K. Differential evolution and swarm intelligence techniques for analog circuit synthesis[C]//2009 World Congress on Nature % Biologically Inspired Conputing. India, 2009: 468-474.
Powell M J D.An efficient method for finding the minimum of a function of several variables without calculating derivatives[J].Computer Journal, 1964, 7(2):155-162. DOI: 155
Meng X B, Liu Y, Gao X Z, et al. A new bio-inspired algorithm: chicken swarm optimization[C]//5th Interational Conference on Swarm Intelligence. Berlin, Hdfei: Springer International Publishing, 2014: 86-94.