High–dimensional optimization problems appear very often in demanding applications. Although evolutionary algorithms constitute a valuable tool for solving such problems, their ...
Abstract. In this work, a Simulated Annealing (SA) algorithm is proposed for a Metabolic Engineering task: the optimization of the set of gene deletions to apply to a microbial str...
This paper introduces Dafo, a new multi-agent framework for evolutionary optimization relying on a competitive coevolutionary genetic algorithm, aka LCGA (Loosely Coupled Genetic A...
We present a multi-objective genetic algorithm for mining highly predictive and comprehensible classification rules from large databases. We emphasize predictive accuracy and comp...
— Memetic algorithms (MAs) combine the global exploration abilities of evolutionary algorithms with a local search to further improve the solutions. While a neighborhood can be e...
Thomas Michelitsch, Tobias Wagner, Dirk Biermann, ...