Multi-objective optimization model for routing flexibility and long-term EV sustainability

This study is motivated by the tactical and operational challenges faced by companies managing electric vehicle (EV) fleets, where battery capacity limits and maintenance battery (MB) operations significantly reduce feet availability. To minimize the number of vehicles used and the frequency of MB activities, transport tasks must be properly allocated, and the variability in battery usage due to environmental and operational conditions must be taken into account. A mathematical model is proposed to support tactical planning by reassigning tasks across vehicles to optimize long-term usage and reduce maintenance frequency. The model addresses a research gap by integrating elements seldom considered together in existing studies on the electric vehicle routing problem (EVRP). It captures long-term effects of task allocation on battery degradation, including charge-discharge cycles over time. Transport tasks are modeled as sequences carried out by multiple vehicles in coordination, rather than assigned to a single vehicle. The objective is minimizing MB operations, emphasizing battery longevity and system efficiency over short-term energy or charging costs. This model may support intelligent systems by enabling sustainable planning and environmentally responsible strategies in EV operations, advancing data-driven solutions in electric mobility.