Global optimization of some difficult benchmark functions by cuckoo-hostco-evolution meta-heuristics
This paper proposes a novel method of global optimization based on cuckoo-host co-evaluation. It also develops a Fortran-77 code for the algorithm. The algorithm has been tested on 96 benchmark functions (of which the results of 30 relatively harder problems have been reported). The proposed method is comparable to the Differential Evolution method of global optimization.
|Date of creation:||11 Aug 2012|
|Date of revision:|
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Web page: https://mpra.ub.uni-muenchen.de
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- Viswanathan, G.M & Bartumeus, F & V. Buldyrev, Sergey & Catalan, J & Fulco, U.L & Havlin, Shlomo & da Luz, M.G.E & Lyra, M.L & Raposo, E.P & Eugene Stanley, H, 2002. "Lévy flight random searches in biological phenomena," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 314(1), pages 208-213.
- Mishra, SK, 2006.
"Performance of Differential Evolution and Particle Swarm Methods on Some Relatively Harder Multi-modal Benchmark Functions,"
1743, University Library of Munich, Germany.
- Mishra, SK, 2006. "Performance of Differential Evolution and Particle Swarm Methods on Some Relatively Harder Multi-modal Benchmark Functions," MPRA Paper 449, University Library of Munich, Germany.
- Mishra, Sudhanshu, 2006. "Some new test functions for global optimization and performance of repulsive particle swarm method," MPRA Paper 2718, University Library of Munich, Germany.
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