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Task scheduling in the cloud is a difficult optimization challenge. The cloud system is assigned with a specific load based on the cloud architecture and user demands. However, both underloaded and overloaded situations result in a variety of system failures in terms of power consumption, machine failure, and so on. As a result, task-load balancing on virtual machines (VMs) is considered as an important part of cloud task scheduling. The present study proposes a dynamic load balancing algorithm based on the hybrid optimization algorithms named as Mantaray modified multi-objective Harris hawk optimization (MMHHO). The hybridization process updates the search space of Harris Hawk Optimization (HHO) by utilizing the Manta Ray Forging Optimization (MRFO) algorithm by considering the cost, response time, and resource utilization etc. The hybrid scheme, proposed in the present study, improves the system …