This paper presents the application of one of the latest swarm intelligence algorithms, the grey wolf optimizer, for solving economic dispatch problems that are nonlinear, non-convex and discontinuous in nature, with numerous equality and inequality constraints. Grey wolf optimizer is a new metaheuristic algorithm that is loosely based on the behavior of the grey wolves. The optimizer has been hybridized to include crossover and mutation for better performance. Four economic dispatch problems (6, 15, 40, and 80 generators), with prohibited operating zones, valve point loading effect and ramp rate limit constraints have been solved, with and without transmission losses. The losses are calculated using B-coefficients. The results obtained are compared with those reported using other methods in the literature. The comparisons show that the hybrid grey wolf optimizer used in this paper either matches or outperforms the other methods. © 2016 Elsevier Ltd.