The large requirement of power for fulfilling daily demands cannot be supplied with the help of a single unit or stored power, a large number of generating units are required to complete this demand. The scheduling of these units so as to generate the forecasted power at a minimum cost is known as Unit commitment problem. It is one of the basic optimization problems in power systems. Different algorithms like lagrangian relaxation, particle swarm optimization and genetic algorithm etc. have been used to address this problem. In this paper a better solution to Unit Commitment problem is proposed. The proposed JayaDE algorithm is a hybrid of Jaya optimization algorithm and Differential Evolution algorithm. The proposed solution results in minimum generation cost as compared to cost involved while using other existing optimization algorithms. Results are shown for 10, 20 and 40 unit system and comparison of total cost and total computational times are listed for different algorithms. © 2016 IEEE.