[en] A new formulation of a nuclear core design optimization problem is introduced in this article. Originally, the optimization problem consisted in adjusting several reactor cell parameters, such as dimensions, enrichment and materials, in order to minimize the radial power peaking factor in a three-enrichment zone reactor, considering restrictions on the average thermal flux, criticality and sub-moderation. Here, we address the same problem using the minimization of the fuel and cladding materials costs as the objective function, and the radial power peaking factor as an operational constraint. This cost-based optimization problem is attacked by two metaheuristics, the standard genetic algorithm (SGA), and a recently introduced Metropolis algorithm called the Particle Collision Algorithm (PCA). The two algorithms are submitted to the same computational effort and their results are compared. As the formulation presented is preliminary, more elaborate models are also discussed (author)