Molecular motors are natural nanomachines that use the free energy released from ATP hydrolysis to generate mechanical forces. Cytoplasmic dynein motors often work collectively as a team to drive important processes such as axonal growth, proplatelet formation and mitosis, as forces generated by single motors are insufficient. A large team of dynein motors is used to slide cytoskeletal microtubules with respect to one another during the process of proplatelet formation and axonal growth. These motors attach to a cargo microtubule via their tail domains, undergo the process of detachment and reattachment of their head domains on another track microtubule, while sliding the cargo microtubule along the track. Traditional continuum/mean-field approaches used in the past are not ideal for studying the sliding mechanism of microtubules, as they ignore spatial and temporal fluctuations due to different possible distributions of motor tails on cargo filament, as well as binding/unbinding of motors from their track. Therefore, these models cannot be used to address important questions such as how the distribution of motor tails on microtubules, or how the mutual exclusion of motor heads on microtubule tracks affects the sliding velocity of cargo microtubule. To answer these, here we use a computational stochastic model where we model each dynein motor explicitly. In our model, we use both random as well as uniform distributions of dynein motors on cargo microtubule, as well as mutual exclusion of motors on microtubule tracks. We find that sliding velocities are least affected by the distribution of motor tails on microtubules, whereas they are greatly affected by mutual exclusion of motor heads on microtubule tracks. We also find that sliding velocity depends on the length of cargo microtubule if mutual exclusion among motor heads is considered.