Evolutionary Algorithm for Large Scale Problems

Evolutionary algorithms (EAs) are a largely used search and optimization technique. They have been successfully applied to a wide variety of problems, overcoming traditional algorithms in performance. However, few EAs and traditional algorithms are able to handle complex combinatorial problems involving a large number of variables (thousands or millions). This paper proposes a new EA, capable of solving combinatorial problems with large number of variables. This algorithm is the result of two extensions from the extended compact genetic algorithm, a state-of-the-art EA.