In traditional environments, optimization of assets, services, and other elements are done on a case-by-case basis. Such an approach produces very specialized solutions for each problem, which are hard to generalize and maintain. Even small changes in the problem definition may require a large amount of effort to modify the solution. Therefore, the cost and time of development and maintenance of such solutions can be very high. With the advent of software-defined networks (SDNs) and virtual functions (VFs), cloud-like environments brings a high degree of automation. Services, assets, and other elements in the datacenter, network, even in the client side, are model-driven and constraints can change on-the-fly. This agile environment requires model-driven solutions that are general and can be adapted in a flexible manner. This disclosure offers a methodology and describes a prototype of a framework to deal with such a model-driven approach to solving optimization problems. The framework is generic enough to tackle many different problems though automatic model creation and optimization.