The smart grid makes use of two-way streams of electricity and information to constitute an automated and distributed energy delivery network. Coming up with multi-agent systems for resource allocation, chiefly comprises the design of local capabilities of single agents, and therefore, the interaction and decision-making mechanisms that make them create the best or at least an acceptable power allocation. Due to the several issues in providing sustainable and affordable power energy, researchers try to think about creating a decentralized mechanism to be able to manage the entire transactions in retail electricity markets. As a result, this electricity infrastructure is predicted to develop into a market of markets, during which all the trading agents influence on each other and have role in toward an equilibrium one. In these markets, we are interested to minimize the buyers’ purchasing cost. Motivating this issue, we model the demand response problem in an evolutionary optimization framework and propose an evolutionary algorithm for handling the decentralized market-based resource allocation problem.