Reverse Distribution Networks are designed to plan the distribution of products from customers to manufacturers. In this paper, we study the problem with two-levels,with products transported from origination points to collection sites before being sent to a refurbishing site. The optimization of reverse distribution networks can reduce the costs of this reverse chain and help companies become more environmentally efficient. In this paper we describe heuristics for deciding locations, algorithms for defining routes, and problem-specific genetic operators. The results of a comparative analysis of 11 algorithms over 25 problem instances suggest that genetic algorithms hybridized with simplex routing algorithms were significantly better than the other approaches tested.