According to the European Energy Performance of Buildings Directive (EPBD-2010/31/EU), all EU-Member states are obliged to continuously apply analysis on cost-optimal levels of minimum energy performance requirements towards nearly/net zero energy buildings. To perform such techno-economic analysis, a large number of technical/financial assumptions should be covered and possibly billions of design/operation options should be explored. This is computationally expensive. This study introduces a novel multi-aid optimization scheme (MAOS) for supporting robust cost-optimal decisions on energy-performance levels of buildings. The scheme's feature is reduction of the computational cost by avoiding time-consuming simulations through the use of post-processing and/or simplified models (when possible), while holistic optimization is adopted for considering multivariate interactions between possible design/operation options and financial/technical assumptions. The effectiveness of MAOS is demonstrated by optimizing a single-family house under 108-financial scenarios, where more than 1.610 solutions would be possible. The results show significant (~95%) time reduction compared with those of the usual simulation-based optimization approach.