Demand Side Management (DSM) has emerged as a critical component of within smart grid frameworks to optimize energy efficiency and mitigate peak load scenarios, and facilitate the integration of renewable energy sources. With the evolution of smart grids, advanced communication infrastructures, intelligent control algorithms, and dynamic pricing mechanisms have significantly transformed DSM strategies. This study explores demand side management by examining its key concepts, goals, and implementation practices, while highlighting pricing-based demand response, optimized appliance scheduling, and smart energy management systems. The review synthesizes recent research contributions covering heuristic, metaheuristic, and artificial intelligence–based approaches, including game theory, evolutionary algorithms, and deep reinforcement learning. The review places special focus on residential DSM, electric vehicle integration, and energy storage technologies, while also outlining major challenges, open research problems, and future research opportunities relevant to researchers and industry professionals.