Enhancement of Multiobjective Search: A Jumping-Genes Approach

Inspired by the gene transposition in biological genome, recently, a new evolutionary computing algorithm has been developed for optimization. It consists of two newly designed operations: copy-and-paste and cut-and-paste, which have been proven mathematically on the basis of schema theory. In this paper, their uniqueness for balancing the exploration and exploitation searching effect is explained. In the meantime, the enhancement of searching efficiency for the multiobjective problems is demonstrated. Its ability is further reinforced by a real world application for a microstrip patch antennae design. The obtained results indicated that this new algorithm is indeed beneficial for gaining a much improved non-dominated solutions front as compared with those derived from the conventional method.