The complexity of the short-term hydrothermal scheduling (STHS) lies in its optimization problem, which considers the transmission losses and valve-point effect (VPE). This problem is characterized by nonlinearity and non-smoothness, which significantly enhance the level of complexity in finding a solution. In order to address the aforementioned issues, the authors have made enhancements to the Grey Wolf Optimization (GWO) by integrating methods from the Sine Cosine Algorithm (SCA). This integration has resulted in the development of a hybrid Modified Grey Wolf Optimizer Sine Cosine Algorithm (MGWOSCA) algorithm, which aims to effectively solve the STHS problem. Proposed algorithm offers faster convergence and avoid local minima. Furthermore, the difficult equality restrictions of STHS are addressed using a specialized repair process, as opposed to use the penalty function approach. The efficacy of the methodology is shown by a test system that has been published in the research literature. The findings are also compared with those acquired by other evolutionary approaches. The suggested technique has shown impressive fuel cost and performance outcomes. The results obtained demonstrate that the MGWOSCA technique offers a superior solution with less computing time and effort.