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DE\BBO is the combination of differential evolution and biogeography based optimization algorithm to get a better optimization algorithm in terms of convergence speed. In DE\BBO, constant crossover rate has been used which sometimes affect the performance of the hybrid algorithm leading to increase in convergence speed. To cope up with this problem, variable crossover rate has been introduced in the hybrid algorithm helping in removing the problem of constant crossover rate. Modified algorithm has been named as DE\BBO\L in which local search mutation and variable crossover rate are used. Testing of BBO, DE\BBO\rand\1 and DE\BBO\L has been performed on different test functions. The results reveal that DE\BBO\L with variable crossover rate is better than DE\BBO with constant crossover rate.

Diversion of Constant Crossover Rate DE\BBO to Variable Crossover Rate DE\BBO\L