Abstract
This paper utilizes a recently developed novel biologically-inspired krill herd algorithm to solve combined heat and power economic emission dispatch optimization problem. Herding behavior of krill individuals is considered to formulate this algorithm. The objective function is defined by the distances of each individual krill from food and from highest density of the herd. The instantaneous position of the krill individual is determined by the: i) movement induced by neighboring krill individuals, ii) foraging activity of it and iii) its random diffusion motion. A test system has been considered in this paper to illustrate this algorithm and the results are compared with those of strength parete evolutionary algorithm 2 (SPEA 2), non-dominated sorting genetic algorithm-II (NSGA II) and real coded genetic algorithm (RCGA). The result shows that this algorithm is capable of solving such multi-objective optimization problem with better convergence consuming less computation time.
Published Version
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