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Environmental/economic dispatch (EED) problems play a salient role in the power system, which can be defined as a complex constrained optimization problem. Many different methods have been introduced to handle EED problems and got some inspiring positive results in the research. In this paper, a new multiobjective global best artificial bee colony (ABC) algorithm is proposed to tackle multiobjective EED problems. To manipulate this problem effectively, we propose a global best ABC algorithm to generate the new individual to speed up the convergence of the proposed algorithm. Afterwards, a crowding distance assignment approach is employed to evolve the population. Finally, a straightforward constraint checking procedure is used to tackle those different constraints of EED problems. Experimental results can conclude that MOGABC can provide best solutions in solving multiobjective EED problems.

Multiobjective Environment/Economic Power Dispatch Using Evolutionary Multiobjective Optimization