Our paper deals with a combinatorial optimization problem called the Optimal Network and Quadratic Assignment Problem. The problem has been introduced by Marc Los [18] as a model of an urban planning problem that consists in optimizing simultaneously the best location of the activities of an urban area (land-use), as well as the road network design (transportation network) in such a way to minimize as much as possible the routing and network costs. We propose a mixed-integer programming formulation of the problem, and a hybrid algorithm based on greedy and evolutionary heuristic methods. Some numerical experiments on randomly generated instances, and on real-life big data from Dakar city, show the efficiency of the method.