A Multiparent Version of the Parent-Centric Normal Crossover for Multimodal Optimization

A new multiparent parent-centric crossover (mPNX), which is a development of a previous two-parent operator called the Parent-centric Normal crossover (PNX), is presented. Both crossovers are studied in combination with the SPC population model. The resulting genetic algorithms (GAs) are tested on a benchmark of particularly hard, nonseparable, shifted, multimodal analytical optimisation problems. This benchmark contains notoriously difficult test problems, which have been already attempted by a number of high quality optimisation methods with limited success. It is shown that the multiparent GA (SPC-mPNX) generally results in significant improvements with respect to the two-parent GA (SPC-PNX), while solving for the first time one of the used test problems.