No abstract

 Abstract: Generating optimal task scheduling plans in cloud environments is a tedious task as it is a np-hard problem. The optimal resource allocation in cloud environments involves more search space and time consuming. Therefore, recent researchers are focused on implementation of artificial intelligence to solve task scheduling problem. In this paper, a new and efficient evolutionary algorithm named teaching-learning based algorithm has been implemented first time to solve the task scheduling problem in cloud environments. The current research work considers the task scheduling problem as a multi-objective optimization problem. The proposed algorithm finds the best solution by minimizing the execution time and response time while maximizing the throughput of all resources to complete the assigned tasks.Index Terms: teaching-learning based optimization, task scheduling, cloud computing, multi-objective optimization, resource allocation and throughput.environments. The results showed that the proposed TLBO algorithm obtains the best solution in less number of iterations even for the cloud environments with huge search space.