Multi-Objective Optimization and Decision-Making for Differentiated Retrofitting of Existing Residential Buildings in Cold Climate Regions

Differences in area, orientation, and spatial organization within a residential community alter heat loss, solar heat gain, and daylighting. Uniform retrofit schemes may underperform for some floor plans. This study aims to develop a differentiated retrofit decision-making method at the floor plan scale and relate baseline performance deficiencies to retrofit responses. Three representative prototypes in Tianjin were modeled under consistent conditions to compare baseline deficiencies, retrofit responses, and strategies. Multi-objective optimization (MOO) used energy use intensity (EUI), total thermal discomfort hours (TDH), and useful daylight illuminance (UDI). The NSGA-II algorithm generated Pareto and Near-Pareto candidate solutions, which were screened against baseline performance deficiencies and ranked by entropy-weighted TOPSIS with initial investment; highly ranked solutions were checked for seasonal performance. EUI decreased by 5.64%, 5.35%, and 4.56%; TDH by decreased 2.02%, 0.95%, and 0.47%; and UDI increased by 6.66%, 17.27%, and 6.76%. Exterior wall insulation and improved balcony exterior windows were common measures. North–south two-bedroom units balanced energy, thermal comfort, and daylighting; east–west units emphasized thermal comfort and daylighting; compact south-facing one-bedroom units prioritized energy reduction while maintaining daylighting and controlling summer thermal risk. The method shows potential for differentiated retrofit decision making under similar climate and construction conditions.