Energy optimization is crucial for reducing environmental impact, cutting operating expenses, and ensuring sustainable resilience in building design and HVAC systems, all aimed at minimizing environmental footprint while maintaining cost-effectiveness and long-term viability. To do so, utilizing algorithms for multi-objective optimization in building envelope and HVAC system design enhances energy efficiency, indoor comfort, and sustainability by concurrently optimizing diverse performance criteria and cutting down costs. This research study examines the multi-objective optimization of envelope design in high-rise apartment complexes located in warm, humid areas with the goal of improving operating energy efficiency and reducing CO₂ emissions using rigorous simulation-based assessments. Two different approaches are used: a genetic algorithm that is implemented in DesignBuilder and a custom multi-objective genetic algorithm (MOGA) with data collected with the help of IoT devices created in-house. An extensive comparative analysis clarifies each method's effectiveness in reaching sustainable building performance. Results show that DesignBuilder's genetic algorithm continuously produces better outcomes, which encourages more research into its underlying mechanics for a more thorough understanding. Furthermore, the customized MOGA provides chances for improvement and optimization, such as algorithmic improvements and parameter calibration. Through a comprehensive analysis of the knowledge obtained from both approaches, this study advances envelope design optimization techniques and informs sustainable building approaches for warm, humid regions. This makes it possible to identify effective routes towards low-carbon and sustainable practices.