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Opposition-based krill herd algorithm applied to economic load dispatch problem
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DOI：10.1016/j.asej.2016.02.003.png)
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Abstract
En 中文
Economic load dispatch (ELD) is the process of allocating the committed units such that the constraints imposed are satisfied and the production cost is minimized This paper presents a novel and heuristic algorithm for solving complex ELD problem, by employing a comparatively new method named krill herd algorithm (OKHA). KHA is nature-inspired metaheuristics which mimics the herding behaviour of ocean krill individuals. In this article, KHA is combined with opposition based learning (OBL) to improve the convergence speed and accuracy of the basic KHA algorithm. The proposed approach is found to provide optimal results while working with several operational constraints in ELD and valve point loading. The effectiveness of the proposed method is examined and validated by carrying out numerical tests on five different standard systems. Comparing the numerical results with other well established methods affirms the proficiency and robustness of proposed algorithm over other existing methods. (C) 2016 Ain Shams University. Production and hosting by Elsevier B.V.
Keywords:
Economic load dispatch
Valve point loading
Opposition based learning
Krill herd algorithm
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