In the current scenario, where the industries are plagued with global energy crisis and skyrocketing fuel prices, the need of the hour is efficient utilization of the available resources without compromising the demand. Several traditional approaches like lambda-iteration and gradient method were utilized in solving non-linear problems. Recently, soft-computing techniques have received attention and have already been applied successfully for many practical applications. Evolutionary programming is an efficient optimization tool for solving non-linear programming problems. In this paper, nature inspired algorithms such as Bacterial Foraging Optimization Algorithm (BFOA) and Firefly Algorithms (FA) were implemented to Economic Load Dispatch (ELD) problem for three generator system and thirteen generator systems with both inclusion and omission of valve point loading. The results obtained are by applying both the algorithms separately to the ELD problem. By comparing other optimization algorithm techniques, we can observe the dominance of the proposed algorithms and confirm their potentiality in solving non-linear ELD issues.
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