Demand-side management (DSM) is a key tool for the energy providers and consumers, and it can use to change the load profile in the modern world. As a result of DSM, the number of new generators compared to energy-side suppliers decreases. In this study, DSM is solved using modified genetic algorithm in reshaping the load profile of commercial, residential, and industrial customers. The DSM is incorporated with unit commitment (UC). Utilizing a hybrid approach, the optimization problem associated with UC is resolved by finding the best possible compromise between two conflicting objectives while upholding system restrictions. The hybrid technique combines the population variant differential evolution (PVDE) algorithm with the nondominant sorting genetic algorithm ii (NSGA–II). Using the IEEE 39 bus system, the suggested hybrid method's potential is evaluated. In contrast to the methods found in the literature currently in use, the suggested method’s outcome highlights a more significant reduction in both total cost and emission values.