An integrated simulation-optimization model and multi-criteria decision-making model for determining of e-vehicle fleet

The advancement of technology and digitalization is progressing rapidly. Nowadays, many products can be readily accessed with great speed. The use of mobile applications has increased, leading to a rise in the number of orders, which in turn will increase the density of vehicles used in the last phase of the transportation system that involves the delivery of orders from the company to the customer. This intensity in last-mile will also increase the emission of harmful gases from the combustion of fossil fuels. Companies need to integrate alternative green vehicles into their transportation systems in order to reduce environmental damage without falling behind in the competition. In this study, the vehicle fleets that will meet the companies' CO2 emission and delivery cost minimization targets as they transition to electric vehicles were identified using the simulation-optimization model. The study focused on analyzing three different drone capacities, as well as e-motorcycles and classic motorcycle. Additionally, seven scenarios were developed to evaluate five various vehicle modes. TOPSIS approach was used to determine the most suitable scenario, taking into account CO2 emission, delivery cost and investment costs. The use of medium-capacity drones and e-motorcycles has been determined as the highest priority scenario.