System for hybridized efficient genetic algorithms to solve bi-objective optimization problems with application to network computing

摘要

A system and methods are presented for the generation of hybridized efficient genetic algorithms (EGAS) applied to bi-objective optimization problems. Applications are made to engineering systems involving collective behaviors, including network computing, robotics and evolvable hardware.