Multi-objective optimization of smart multifunctional self-sensing cementitious composite incorporating biomass waste derived high-carbon biochar

• Corn cob biochar achieved 93.6 wt% carbon via 450°C pyrolysis • Optimal formulation: 85.2 MPa strength with 855 Ω·m resistivity • Piezoresistive response R²=0.994 over 0-30 MPa stress range • Multi-objective optimization: 46 Pareto solutions, R²>0.983 models Multi-objective optimization of cementitious composites for intelligent infrastructure applications has been emerging as promising solution, as conventional design approaches focus on single properties rather than simultaneous optimization of mechanical, electrical, and environmental performance. This study developed a comprehensive multi-objective optimization framework integrating Taguchi L25 orthogonal array experimental design with Non-dominated Sorting Genetic Algorithm II (NSGA-II) to systematically optimize biochar-enhanced self-sensing cement composites. Corn cob-derived biochar was synthesized through controlled slow pyrolysis at 450°C, achieving 93.6 wt% carbon content and eliminating the need for fossil fuel additives. The Taguchi design systematically evaluated 25 mix combinations across water-to-cement ratios (0.20-0.40) and biochar contents (1.0-3.0 wt%), yielding comprehensive experimental data for model development. NSGA-II optimization generated 46 non-dominated Pareto solutions spanning compressive strengths of 68.5-96.9 MPa and electrical resistivities of 438-1296 Ω·m, with excellent convergence characteristics (hypervolume 92.4%). The ideal point method identified the optimal formulation (w/c = 0.280, biochar = 3.0 wt%) achieving 85.2 MPa compressive strength, 855 Ω·m electrical resistivity, and gauge factor of 28.5 for structural health monitoring applications. Accelerated carbonation testing quantified 55.5 kg CO₂/m³ sequestration capacity, representing 122% improvement over conventional concrete. This multi-objective concrete optimization framework transforms cementitious composites into smart materials for intelligent infrastructure.