Digital microfluidic biochips, (DMFBs), are designed to carry out several biochemical and biomedical studies quickly and effectively in terms of accuracy and time in a very small space. DMFBs provide a variety of advantages over traditional laboratory techniques, including cost reductions, enhanced automation, software programmability, and almost 100% precision. The scheduling of microfluidic activities, like floor-planning and pin assignment, module placement, droplet routing, mixing operations are the very basic and the most crucial steps in the fluidic-level synthesis of DMFBs. The scheduling problem of DMFB mixing operations is an NP-complete multi-constrained optimisation problem. For the purpose of scheduling of DMFB operations, here we suggest a hybrid BAT algorithm. The proposed BAT* algorithm moves through the search space, considers several possible schedules, and then returns the best schedule out of those considered. Simple list-based scheduling heuristics can explore a single schedule depending on the sequence that the priority function generates. Search techniques based on iterative improvement traverse the whole search space and consider more schedules, but the suggested BAT* algorithm generates desired solutions in a shorter amount of time. The proposed BAT* generates more optimum completion time and has a quicker execution time than current algorithms, according to several benchmark simulation findings. Here, finally hexagonal DMFBs (HDMFB) are also considered which results in a hugely better completion time over traditional square DMFBs in respect of routing flexibility and mixing quality. Eventually, a comparison of assay completion time is shown, which ultimately conforms that, hexagonal DMFBs perform better in case of total bioassay execution.