The demand-side management (DSM) is one of the most important aspects in future smart grids: towards electricity generation cost by minimizing the expensive thermal peak power plants. The DSM greatly affects the individual users' cost and per unit cost. The main objective of this research article is to develop a generic demand-side management (G-DSM) model for residential users to reduce peak-to-average ratio (PAR), total energy cost, and waiting time of appliances (WTA) along with fast execution of the proposed algorithm. We propose a system architecture and mathematical formulation for total energy cost minimization, PAR reduction, and WTA. The G-DSM model is based on genetic algorithm (GA) for appliances scheduling and considers 20 users having a combination of appliances with different operational characteristics. Simulation results show the effectiveness of G-DSM model for both single and multiple user scenarios. Copyright (c) 2015 John Wiley & Sons, Ltd.