This study addresses the critical issue of optimizing the location and capacity planning of electric vehicle charging stations (EVCS) to enhance the adoption of electric vehicles (EVs). The authors propose a comprehensive approach that integrates location modeling with demand forecasts and market penetration. They use a genetic algorithm to solve the p-median problem for location selection and Arena 14 simulation software to model station traffic and optimize charging unit types and quantities. The model prioritizes public areas, considering potential demand points and station locations to propose optimal charging areas. The results indicate that the model minimizes travel distances and waiting times, offering a scalable solution adaptable to future EV market growth. The study contributes to the field by presenting a sustainable and economical model for EVCS placement and capacity planning, emphasizing the importance of a robust charging network in the broader adoption of electric transportation. The findings suggest that proactive infrastructure development, guided by accurate demand predictions and optimized location strategies, can significantly enhance the feasibility and attractiveness of EVs, supporting global efforts towards a cleaner, more sustainable transportation system.This study addresses the critical issue of optimizing the location and capacity planning of electric vehicle charging stations (EVCS) to enhance the adoption of electric vehicles (EVs). The authors propose a comprehensive approach that integrates location modeling with demand forecasts and market penetration. They use a genetic algorithm to solve the p-median problem for location selection and Arena 14 simulation software to model station traffic and optimize charging unit types and quantities. The model prioritizes public areas, considering potential demand points and station locations to propose optimal charging areas. The results indicate that the model minimizes travel distances and waiting times, offering a scalable solution adaptable to future EV market growth. The study contributes to the field by presenting a sustainable and economical model for EVCS placement and capacity planning, emphasizing the importance of a robust charging network in the broader adoption of electric transportation. The findings suggest that proactive infrastructure development, guided by accurate demand predictions and optimized location strategies, can significantly enhance the feasibility and attractiveness of EVs, supporting global efforts towards a cleaner, more sustainable transportation system.