Real-coded genetic algorithm with uniform random local search

Genetic algorithms are efficient global optimizers, but they are weak in performing fine-grained local searches. In this paper, the local search capability of genetic algorithm is improved by hybridizing real coded genetic algorithm with 'uniform random' local search to form a hybrid real coded genetic algorithm termed 'RCGAu'. The incorporated local technique is applied to all newly created offspring so that each offspring solution is given the opportunity to effectively search its local neighborhood for the best local optimum. Numerical experiments show that the performance of RCGA is remarkably improved by the uniform random local search technique.