Retailer Fleet Mix Optimization: Economic and Environmental Impacts Across Different Scenarios

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. The analysis offers actionable insights and recommendations tailored to the company’s current business environment, supporting its sustainability and budget goals for 2030. Pareto frontiers were generated for multiple scenarios, considering the company’s existing fleet and requirements, future EU regulations, and strategies to address compliance challenges. Additionally, alternative scenarios account for external effects, acknowledging their potential to significantly influence decision-making. Time-series models were also developed to predict fuel prices, enhancing the strategic value of the recommendations. Key findings highlight that the trade-off between environmental and economic performance is unbalanced, with limited cost increases leading to significant sustainability improvements. From a theoretical perspective, this research contributes to the academic discourse on sustainable fleet optimization by integrating multi-objective optimization with real world operational constraints and regulatory frameworks into decision-making models, offering a methodology that can be adapted to face similar challenges. The results from the study provide practical solutions for fleet mix allocation, equipping the supermarket company with strategies to achieve its sustainability objectives while aligning with regulatory mandates and mitigating operational risks.