Resources are offered to customers on demand in the modern era of computing, communication, and technology. User demand of the resources depends on service provider and consumer. The optimal assignment of the cloud resources depends on fitness function and resource management technique. In this manuscript, the key focus is to proposed a model based on meta-heuristic evaluation technique. The meta-heuristic evaluation technique provides an optimal placement of the virtual machines to the user requests across the globe. The presented framework, elephant heard optimization with neural network (EHO-ANN) outperforms the existing static, dynamic and nature inspired techniques. The EHO-ANN is evaluated and analyzed against Max-Min, Genetic Approach and BB-BC cost aware approach. The evaluation and analysis include the performance metric, average execution time(ms), and cost.