Process variations lead to a significant degradation of IC parametric yield

and they also tend to cause a negative correlation between different parametric yields.However

previous yield optimization works are limited to deal with single objective problem.To deal with the above-mentioned limitation

this paper proposes a multi-objective optimization framework for co-optimization of power and timing yields under process variations.The proposed method starts with establishing explicit statistical models for power and timing metrics respectively.Then considering the negative correlation between the metrics

we employ Chebyshev affine arithmetic to formulate a multi-objective optimization model

optimize power and timing yields simultaneously by adaptive weighted sum method

and provide a well-distributed set of Pareto-optimal solutions.Experimental results demonstrate that the proposed method explores about 30 well-distributed solutions for each benchmark circuit with different test units.In addition

it can not only balance the restricted correlation between multiple optimization objectives

but make the traditional weighted sum method to get optimal solutions on the Pareto curve where change rate is small.