Enhancing the search ability of differential evolutionary through partial intermediate recombination

Differential Evolution (DE) is a simple yet efficient stochastic algorithm for solving real world problems. Binomial crossover and exponential crossover are two commonly used crossover operators in current popular DE. It is noteworthy that these two operators can only generate a vertex of a hypercube defined by the mutant and target vectors. In this paper, using intermediate recombination to generate an offspring within the hypercube is proposed, named Intermediate Recombination Differential Evolution (IRXDE). In this method, intermediate recombination can make a systematic search in a hypercube defined by the parent solutions. The proposed strategy has been evaluated on a test-suite of 20 benchmark functions. The results of the experiments indicate that IRXDE is competitive with respect to some other DE strategies.