For the purpose of reducing electricity cost and peak to average ratio (PAR), different electricity consumers have now an opportunity to schedule their electrical tasks. In this paper, we comparatively evaluated the performance of three meta-heuristic algorithms for our proposed Home Energy Management system (HEMS) i.e., Enhanced Differential Evolution (EDE), Harmony Search Algorithm (HSA), and Tabu Search (TS). The HEMS presented in this paper is based on Demand Side Management (DSM) and involvement of electricity consumers of a residential area domain to consider major factor of user satisfaction. In order to tackle the pricing for electricity bill calculation, a combined model of time of use (ToU) and critical peak pricing (CPP) is used. To deal with the scheduling of appliances a defined classification of appliances is taken from a part of literature. Simulation results verified that proposed techniques performed competently in achieving the above mentioned objectives.