Cooperative Co-Evolutionary Cuckoo Search Algorithm for Continuous Function Optimization Problems
HU Xin-Xin1,YIN Yi-Long2
1.School of Computer and Information Science,Fujian Agriculture and Forestry University,Fuzhou 350002 2.School of Computer Science and Technology,Shandong University,Jinan 250101
Abstract To improve the performance of cuckoo search algorithm for continuous function optimization problems,a cooperative co-evolutionary cuckoo search algorithm is proposed. Through the framework of cooperative co-evolutionary,the improved algorithm divides the solution vectors of population into several sub-vectors and constructs the corresponding sub-swarms. The solution vectors of each sub-population are updated by the standard cuckoo search algorithm. Each sub-population provides the vectors of the best solution,which are combined with solution vectors of other sub-populations,and the combined solution vectors are evaluated. The simulation experiments on 10 benchmark functions show that the proposed algorithm efficiently improves the performances on contnuous function optimization problems and it is a competitive optimization algorithm for the problems compared with other algorithms.
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2013, Vol. 26 
