Abstract. Theoretical models of Turing complete linear genetic programming (GP) programs suggest the fraction of halting programs is vanishingly small. Convergence results proved f...
This paper investigates the use of genetic programming in automatized synthesis of scheduling heuristics. The applied scheduling technique is priority scheduling, where the next st...
Abstract. A new model for evolving crossover operators for evolutionary function optimization is proposed in this paper. The model is a hybrid technique that combines a Genetic Pro...
This paper introduces a new representation for assemblies of small Lego -like elements: structures are indirectly encoded as construction plans. This representation shows some inte...
Alexandre Devert, Nicolas Bredeche, Marc Schoenaue...
The multi-objective covariance matrix adaptation evolution strategy (MO-CMA-ES) combines a mutation operator that adapts its search distribution to the underlying optimization prob...
In this paper, we propose a new conceptual method for the design, investigation, and evaluation of multi-objective variation operators for evolutionary multi-objective algorithms. ...
With the popularity of efficient multi-objective evolutionary optimization (EMO) techniques and the need for such problem-solving activities in practice, EMO methodologies and EMO ...
In this paper we study a number of issues related to the design of a cellular genetic algorithm (cGA) for multiobjective optimization. We take as an starting point an algorithm fol...