Multi-Objective Vaccine Delivery Problem Considering Low Carbon and Customer Loss Aversion

High infection rates caused by Covid-19 make vaccine distribution increasingly important. However, staff shortages and vehicle resource constraints make vaccine distribution even more difficult. Facing the urgency of vaccine distribution, in addition, the high energy consumption and high carbon emissions of vaccine delivery vehicles require us to think deeply about the vaccine delivery problem. This paper takes the above factors into account and constructs a delivery delay penalty function based on the characteristics of customer behavior for loss aversion. Then, we model minimizing logistics cost that includes carbon emissions cost and cold chain cost. Lastly, we establish a multi-objective optimization model and propose an optimization algorithm that deals with fruit fly optimization that includes simulated annealing algorithm criteria, and verifies the effectiveness of the algorithm through multiple numerical experiments. The results show that we can scientifically configure the logistics route by reducing the usage of delivery vehicles without increasing carbon emissions while achieve to balance both distribution cost and delivery efficiency.