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The economic lot scheduling problem (ELSP) has been studied over 50 years. ELSP is known as NP-hard and hence heuristic algorithms have been developed. In those heuristics, researchers generally adopted two types of rounding-off methods for the production frequency of products, namely, the nearest integer and power-of-two approaches. The production frequency of products defines the number of times that such product being produced during the cycle. Therefore, different production frequency actually leads to different optimization results even for the same set of products. For this reason, this paper proposes a two-level genetic algorithm to deal with this problem. A number of numerical examples found in literature and randomly generated problem sets are used to test and benchmark the performance of the new approach. The comparison shows that the new approach outperforms the other existing approaches and also demonstrates the significance of the production frequency to the optimization results.