Abstract: To address the reliability assessment requirements of multi-stage mission systems, this study proposes an optimized design framework for accelerated degradation testing based on the Wiener degradation model. A mission success probability model is established to analyze the joint effects of load heterogeneity and temporal asymmetry across mission stages. Utilizing the large-sample approximation method, the asymptotic variance of parameter estimation is derived as the optimization objective to determine the optimal test plan. Numerical case studies reveal that high-load stages dominate resource allocation due to their nonlinear degradation characteristics, necessitating increased component allocation to capture rapid degradation patterns. Reduced stage duration amplifies the variance of parameter estimation, requiring a higher proportion of high-load group resources to compensate for data insufficiency. Two compromise rules are further proposed, and quantitative analyses using relative efficiency metrics demonstrate a positive correlation between mission complexity and efficiency loss. The resource-biased strategy achieves superior balance between estimation accuracy and practical constraints, providing actionable suboptimal solutions for engineering applications.