Global Optimization of Some Difficult Benchmark Functions by Host-Parasite Coevolutionary Algorithm
This paper proposes a novel method of global optimization based on host-parasite co-evolution. It also develops a Fortran-77 code for the algorithm. The algorithm has been tested on 100 benchmark functions (of which the results of 32 relatively harder problems have been reported). In its search ability, the proposed method is comparable to the Differential Evolution method of global optimization. The method has been used for solving the 'completing the incomplete correlation matrix' problem encountered in financial economics. It is found that the proposed methods as well as the Differential Evolution method solves the problem, but the proposed method provides results much faster than the Differential Evolution method.
Volume (Year): 33 (2013)
Issue (Month): 1 ()
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