This study presents a multi-objective optimization framework for enhancing environmental performance in high-density residential complexes, addressing the critical balance between sunlight access, visual openness, and ground-level privacy. Applied to Helio City Phase 3 in Seoul—a challenging case with 2026 units surrounded by adjacent blocks—the research developed a sequential three-stage optimization strategy using computational design tools. The methodology employs Ladybug simulations for solar analysis, Galapagos genetic algorithms for view optimization, and parametric modeling for privacy assessment. Through grid-based layout reconfiguration, tower form modulation, and strategic conversion of vulnerable ground-floor units to public spaces, the optimized design achieved 100% sunlight standard compliance (improving from 64.31%), increased average visual openness to 66.31% (from 39.48%), and eliminated all privacy conflicts while adding 30 residential units. These results demonstrate that computational optimization can significantly surpass conventional planning approaches in addressing complex environmental trade-offs. The framework provides a replicable methodology for performance-driven residential design, offering quantitative tools for achieving regulatory compliance while enhancing residents’ experiential comfort in dense urban environments.
Kim et al. (Tue,) studied this question.
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