Multi-objective optimization of double-layered microchannel heat sink based on derivative-free algorithm

In the present study, an optimization model of double-layered microchannel heat sink (DL-MCHS) is developed based on a derivative-free method, BOBYQA algorithm, which solves optimization problems without using derivatives of the objective function. Overall, thermal resistance R-T and pumping power are adopted as multi-objective functions to search for optimal design variables. The effect of weight factors on results of optimization is discussed. With the increase of increases. Moreover, the effect of design variables of the bottom layers on flow and heat transfer performance is more obvious than that of the upper layers. Finally, the Pareto fronts of counter-flow and cross-flow DL-MCHS are calculated. Results indicate that counter-flow heat sink shows better thermal performance compared to cross-flow heat sink under the same pumping power consumption.