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The work in this paper is aimed at demonstrating the practical multiobjective optimization of plate-fin heat sinks and the superiority of using a combined response surface method and multiobjective evolutionary optimizer over solely using the evolutionary optimizer. The design problem assigned is to minimize a heat sink junction temperature and fan pumping power. Design variables determine a heat sink geometry and inlet air velocity. Design constraints are given in such a way that the maximum and minimum fin heights are properly limited. Function evaluation is carried out by using finite volume analysis software. Two multiobjective evolutionary optimization strategies, real-code strength Pareto evolutionary algorithm with and without the use of a response surface technique, are implemented to explore the Pareto optimal front. The optimum results obtained from both design approaches are compared and discussed. It is illustrated that the multiobjective evolutionary technique is a powerful tool for the multiobjective design of electronic air-cooled heat sinks. With the same design conditions and an equal number of function evaluations, the multiobjective optimizer in association with the response surface technique totally outperforms the other. The design parameters affecting the diversity of the Pareto front include fin thickness, fin height distribution, and inlet air velocity while the plate base thickness and the total number of fins of the non-dominated solutions tend to approach certain values.