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Multiobjective fuzzy dominance based bacterial foraging algorithm to solve economic emission dispatch problem
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DOI：10.1016/j.energy.2010.09.014.png)
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This paper proposes the bacterial foraging meta-heuristic algorithm for multiobjective optimization. In this multiobjective bacterial foraging optimization technique, the most recent bacterial locations are obtained by chemotaxis process. Next, Fuzzy dominance based sorting procedure is used here to select the Pareto optimal front (POF). To test the suitability of our proposed algorithm we have considered a highly constrained optimization problem namely economic/emission dispatch. Now-a-days environmental concern that arises due to the operation of fossil fuel fired electric generators and global warming, transforms the classical economic load dispatch problem into multiobjective environmental/economic dispatch (EED) problem. In the proposed work, we have considered the standard IEEE 30-bus six-generator test system and the results obtained by proposed algorithm are compared with the other recently reported results. Simulation results demonstrate that the proposed algorithm is a capable candidate in solving the multiobjective economic emission load dispatch problem. (C) 2010 Elsevier Ltd. All rights reserved.
Keyword:
Multiobjective optimization
Environmental/economic dispatch
Pareto front
Bacterial foraging
Non-dominated sorting
Fuzzy dominance sorting
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9.4
论文数:
4.3W
被引数:
20.2W
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A novel meta-heuristic optimization methodology for solving various types of economic dispatch problem.png)
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