Optimization of MVR System for High‐Salinity Wastewater Treatment Using Genetic Algorithm

ABSTRACT To tackle high energy consumption for high‐salinity wastewater, this study proposes an optimized multi‐effect mechanical vapor recompression (MVR) system for calcium chloride treatment. A hybrid multi‐objective optimization framework was established by integrating a rigorous steady‐state process model with strength Pareto evolutionary algorithm 2 (SPEA2). Exergy evaluation and sensitivity analysis showed that system performance improved with a first‐effect evaporation temperature of 103.64°C and a compressor discharge pressure of 1.9 bar. Under these conditions, the total heat transfer area decreased by 8.22%, energy consumption reduced by 8.61%, and crucially, economic analysis showed a 6.36% reduction. The system also demonstrated a 5.74% improvement in thermal efficiency and a 10.35% decrease in energy loss. These results confirm the proposed framework's effectiveness in balancing thermodynamic efficiency and economic viability, offering a scalable and robust design for industrial retrofitting of high‐salinity wastewater evaporation.