This study presents a multi-objective optimization of a trapezoidal double-layer microchannel heat sink (TDL-MCHS) to minimize both thermal resistance and pumping power. A three-dimensional fluid-solid conjugate heat transfer model, coupled with a multi-objective genetic algorithm, was employed. The optimization considered five design variables, including the flow rate ratio between the upper and lower channels and four geometric parameters related to the channel cross-sections. A parametric study explored the design space, and response surface approximation was applied to improve computational efficiency. The results showed that the optimized TDL-MCHS achieved up to a 42% reduction in thermal resistance, though at the cost of a significant increase in pumping power. Conversely, minimizing pumping power by 42% led to a 4% reduction in thermal resistance. The Pareto-optimal front highlights the trade-offs between thermal performance and energy consumption, providing valuable insights for the efficient design of TDL-MCHSs in electronic cooling applications.
