Differential evolution (DE) is a powerful yet simple evolutionary algorithm for optimizing real valued optimization problems. Traditional investigations with differential evolution...
This paper describes an evolutionary clustering algorithm, which can partition a given dataset automatically into the optimal number of groups through one shot of optimization. The...
Abstract The growing demand for large and complex ontologies present new challenges related to their design, maintenance and evolution. In this paper, we propose an approach to man...
In this paper, we incorporate a diversity mechanism to the differential evolution algorithm to solve constrained optimization problems without using a penalty function. The aim is...
We demonstrate the emergence of collective behavior in two evolutionary computation systems, one an evolutionary extension of a classic (highly constrained) flocking algorithm and...
Lee Spector, Jon Klein, Chris Perry, Mark Feinstei...