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This paper proposes a hybrid method that integrates the main features of particle swarm optimization (PSO) and evolutionary programming (EP) for solution of nonconvex economic load dispatch (ELD) problems having nonlinearities like valve point loadings. Algorithms based on PSO, Evolutionary programming (EP) and PSO embedded EP techniques have been developed and tested on a practical nonconvex ELD problem with valve point loading effects considered in the cost functions. Numerical results show that all the algorithms are capable of finding feasible near global solutions within a reasonable time but PSO embedded EP-algorithm with Gaussian mutation appears to outperform the other two in terms of convergence speed, solution time and quality of solution.