Research on Modified Shifting Balance Genetic Algorithms

The increasing overlap of core and colony populations during the anaphase of evolution may limit the performance of shifting balance genetic algorithms. To decrease such overlapping, so as to increase the local search capability of the core population, the sub-space method was used to generate uniformly distributed initial colony populations over the decision variable space. The core population was also dynamically divided, making simultaneous searching in several local spaces possible. The algorithm proposed in this paper was compared to the original one by searching for the optimum of a complicated multi-modal function. The results indicate that the solutions obtained by the modified algorithm are better than those of the original algorithm.