A new Jumping Genes paradigm is proposed for evolutionary computing. It is speedy and yet capable of generating some extreme solutions within the Pareto front This algorithm emulates the genetic phenomenon of horizontal transmission in which the genes can be jumped from one position to another position either within its own or the other chromosome. This paper describes the concept, methodology and implementation of the algorithm that can be aptly used for evolutionary computing. The performance in simulation based on some standard test functions has demonstrated its effectiveness in multiobjective optimization and its results also have been compared with other algorithms currently in use. © 2004 IEEE.
|Title of host publication||IECON Proceedings (Industrial Electronics Conference)|
|Publication status||Published - 2004|