The purpose of this study is to optimize the dynamicRb-82 myocardial perfusion (MP) PET acquisition/reconstruction protocols for maximum perfusion defect detection using realistic simulation data and task-based evaluation. Time activity curves (TACs) of different organs at both rest and stress conditions were extracted from dynamic Rb-82 PET images of 5 normal patients. Combined SimSET-GATE Monte Carlo simulation was used to generate nearly noise-free (NNF) MP PET data from a time series of 3D NCAT phantoms with organ activities modeling difTerent pre-scan delay times (PDTs) and total acquisition times (TATs). Poisson noise was added to the NNF projections and the OS-EM algorithm was applied to generate noisy reconstructed images. The channelized Hotelling observer (CHO) with 32x32 spatial templates corresponding to 4 octave-wide frequency channels was used to evaluate the images. The area under the ROC curve (AVC) was calculated from the CHO rating data as an index for image quality in terms of MP defec detection. The 0.5 cycle/cm Butterworth post-filtering on OS-EM (with 21 subsets) reconstructed images generates the highest AVC values while those from iteration number 1 to 4 do not show different AVC values. The optimized PDTs for both rest and stress conditions are found to be close to the cross points of the left ventricular chamber and myocardium TACs, which may promote individualized PDT for patient data processing and image reconstruction. Shortening the TATs for <̃3 minutes from the clinically employed acquisition time does not affect the MP defect detection significantly for both rest and stress studies.