The practical economic load dispatch problem is a nonconvex and non-smooth optimization problem. It is challenging for the available optimization solvers to find the global optimal solution to this problem. Therefore, new and superior optimization solvers are still desired. To introduce a novel and efficient optimization solver to the problem, a recently developed generic optimization solver, known as the Honey Badger Algorithm (HBA), is utilized in this paper. The performance of the HBA is enhanced by augmenting it with a random walk-based search mechanism, known as Levy flights, to improve the diversity of the population as the search progresses. The resultant proposed algorithm is denoted as Honey Badger Algorithm with Levy Flights (HBA-LF). Based on two benchmark problems, the proposed algorithm is compared with several state-of-the-art algorithms. The results demonstrate the superiority of the proposed algorithm compared to the previously proposed algorithms. In particular, considering a real benchmark system, the proposed algorithm could achieve a monetary saving that ranges from 243.73 $/hr to 98,253 $/hr if the proposed algorithm has been adopted for solving the problem instead of previously proposed algorithms.