A Jumping Genes Paradigm: Theory, Verification and Applications

A new evolutionary computing algorithm on the basis of "jumping genes" phenomenon is presented in this article. It emulates the gene transposition in the genome that was discovered by Nobel Laureate Dr. Barbara McClintock from her work on maize chromosome. The principle of jumping genes, adopted for evolutionary computing, is outlined and the procedures for executing the computational optimization are provided. Mathematical derivation of the schema theorem is briefly discussed, which is established to demonstrate the searching capacity of the newly proposed algorithm, in terms of convergence and diversity. The algorithm is found to be robust and provides outcomes in speed and accuracy, while the solutions are widely spread along the Pareto-optimal front when a multiobjective problem is tackled. T o further reinforce the jumping genes proposition, some typical engineering design problems are included. The obtained results have indicated that this new algorithm is indeed capable of searching multiobjective solutions including the extreme solutions at both ends of the Pareto-optimal front.