caa a22 4500 605470332 CHVBK 20210128100327.0 cr unu---uuuuu 210128e20150501xx s 000 0 eng 10.1007/s00500-014-1336-3 doi (NATIONALLICENCE)springer-10.1007/s00500-014-1336-3 A mutative-scale pseudo-parallel chaos optimization algorithm [Elektronische Daten] [Xiaofang Yuan, Xiangshan Dai, Lianghong Wu] Chaos optimization algorithms (COAs) utilize the chaotic map to generate the pseudo-random sequences mapped as the decision variables for global optimization applications. Many existing applications show that COAs escape from the local minima more easily than classical stochastic optimization algorithms. However, the search efficiency of COAs crucially depends on appropriately starting values. In view of the limitation of COAs, a novel mutative-scale pseudo-parallel chaos optimization algorithm (MPCOA) with cross and merging operation is proposed in this paper. Both cross and merging operation can exchange information within population and produce new potential solutions, which are different from those generated by chaotic sequences. In addition, mutative-scale search space is used for elaborate search by continually reducing the search space. Consequently, a good balance between exploration and exploitation can be achieved in the MPCOA. The impacts of different chaotic maps and parallel numbers on the MPCOA are also discussed. Benchmark functions and parameter identification problem are used to test the performance of the MPCOA. Simulation results, compared with other algorithms, show that the MPCOA has good global search capability. Springer-Verlag Berlin Heidelberg, 2014 Chaotic map nationallicence Chaos optimization algorithm (COA) nationallicence Parallel chaos optimization algorithm (PCOA) nationallicence Cross operation nationallicence Merging operation nationallicence Yuan Xiaofang College of Electrical and Information Engineering, Hunan University, 410082, Changsha, People's Republic of China aut Dai Xiangshan College of Electrical and Information Engineering, Hunan University, 410082, Changsha, People's Republic of China aut Wu Lianghong College of Information and Electrical Engineering, Hunan University of Science and Technology, 411201, Changsha, People's Republic of China aut Soft Computing Springer Berlin Heidelberg 19/5(2015-05-01), 1215-1227 1432-7643 19:5<1215 2015 19 500 https://doi.org/10.1007/s00500-014-1336-3 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-014-1336-3 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Yuan Xiaofang College of Electrical and Information Engineering, Hunan University, 410082, Changsha, People's Republic of China aut NATIONALLICENCE 700 1- Dai Xiangshan College of Electrical and Information Engineering, Hunan University, 410082, Changsha, People's Republic of China aut NATIONALLICENCE 700 1- Wu Lianghong College of Information and Electrical Engineering, Hunan University of Science and Technology, 411201, Changsha, People's Republic of China aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/5(2015-05-01), 1215-1227 1432-7643 19:5<1215 2015 19 500