The high volume of daily e-commerce shipments in major urban areas require today's technology of drones for last-mile delivery (LMD) of parcels. The traditional method of delivering parcels using trucks is time-consuming due to traffic congestion, impeding their timely delivery. On the other hand, drones can avoid traffic congestion by flying over road networks. However, drones have a limited flight endurance due to their battery capacity constraints. At the same time, trucks possess long-haul capabilities. Hence, for achieving an efficient LMD, both trucks and drones should be integrated to offset each other's disadvantages. This paper addresses one such truck-drone based last-mile delivery (TD-LMD) problem. There are plenty of studies which have investigated TD-LMD problem with different configurations. For our study, we examine the TD-LMD problems involving single depot, single truck and multiple drones (SD-ST-MD) configuration. In the literature, various researchers have used mathematical models and heuristics to address this problem. In our study, we consider one Mixed-Integer Linear Programming (MILP) model given in the existing literature for the TD-LMD problem with SD-ST-MD configuration and relax one of their assumptions to give it a new dimension. In the process of extending the MILP model, we also introduce the CO₂ emission cost along with the economic cost for optimizing the TD-LMD problem. Accordingly, the workability of the MILP model is tested using a tiny numerical example and solved through developing a code in the Python-MILP solver module. Further, the computational complexity is analyzed by increasing the number of nodes in the SD-ST-MD based TD-LMD problem.