Virtual machine placement in a distributed cloud environment becomes more challenging due to the tradeoffs between multiple objectives. Placing a virtual machine to an appropriate physical machine must simultaneously minimize the objectives such as resource wastage, power consumption and network transmission delay. Minimizing an objective may have negative impact on some other objectives. A multiobjective optimization problem is to find a solution where all objective will attain optimality. With the evolution of solutions, the Multiobjective Evolutionary Algorithms has the potential to converge towards pareto-optimal solutions. In this paper, VM placement problem with multi-objectives is addressed using Evolutionary algorithm with Decomposition. The proposed algorithm is compared based on performance indicator such as spacing and ONGV with existing multiobjective Elitist algorithms (SPEA and NSGA-II) and Non-elitist algorithms (VEGA and MOGA) shows significant improvement. © 2020, Springer Nature Singapore Pte Ltd.