During the last years wind energy has experimented a significant growth in comparison with other types of renewable energy sources. Accordingly, the number of wind farms has increased sharply to become one of the most developed worldwide infrastructures. Unfortunately, the high number of constraints and restrictions that must be considered nowadays when designing a wind farm deployment (e.g. protected environmental areas or geographical unfeasibility) calls for tools aimed at the cost-effective optimal placement of wind farms, along with an optimized micro-siting of their compounding wind turbines. In this paper a novel multi-objective adaptation of the Harmony Search meta-heuristic algorithm is developed and tested for efficiently solving the problem of optimally deploying wind turbines in wind farms, which is accomplished by simultaneously addressing two conflicting objectives: the yield production and the capital cost of the deployment. Experimental simulation results over a certain region of the Basque Country (northern Spain) will be presented and discussed so as to shed light on the practical applicability of the derived solver.