As cloud resource demand grows, supply chain management (SCM), which is the core function of cloud computing, faces serious challenges. Quite a number of techniques have been proposed by many researchers for such a challenge. As such, numerous proposed strategies are still under reckoning and modification so as to enhance its potential. An optimized dynamic scheme that combined several algorithms' characteristics was proposed to map out such a challenge. The hybridized proposed scheme involved the meta-heuristic swarm mechanism of ant colony optimization (ACO) and deterministic spanning tree (SPT) algorithm as it obtained faster convergence chain, ensured resource utilization in least time and cost. Extensive experiments conducted in cloudsim simulator provided an efficient result in terms of minimized makespan time and throughput as compared to SPT, round robin (RR), and pre-emptive fair scheduling algorithm (PFSA) as it significantly improves performance.