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Improved multi-objective artificial bee colony algorithm for optimal power flow problem
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DOI：10.1007/s11771-014-2418-1.png)
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Abstract
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The artificial bee colony (ABC) algorithm is improved to construct a hybrid multi-objective ABC algorithm, called HMOABC, for resolving optimal power flow (OPF) problem by simultaneously optimizing three conflicting objectives of OPF, instead of transforming multi-objective functions into a single objective function. The main idea of HMOABC is to extend original ABC algorithm to multi-objective and cooperative mode by combining the Pareto dominance and divide-and-conquer approach. HMOABC is then used in the 30-bus IEEE test system for solving the OPF problem considering the cost, loss, and emission impacts. The simulation results show that the HMOABC is superior to other algorithms in terms of optimization accuracy and computation robustness.
Keywords:
cooperative artificial colony algorithm
optimal power flow
multi-objective optimization
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