The increasing pressure on companies to balance economic efficiency with environmental sustainability has made fleet management a critical sustainability challenge. In the context of a leading supermarket company, optimizing truck and cooler configurations under different fuel types and operational constraints is essential to meeting both cost and carbon reduction goals. This thesis develops a multi-objective optimization model for sustainable fleet management, aimed at minimizing operational costs and carbon emissions for a leading supermarket company. The research focuses on optimizing truck and cooler configurations under various operational constraints and fuel types. By employing the epsilon-constraint method and exploring diverse scenarios, including regulatory, risk management, and operational events, the study evaluates trade-offs between economic and environmental objectives.