The paper proposes a novel nature-inspired swarm algorithm: peacock algorithm (PA). It is based on the lekking and mating behavior of peacocks. The best solutions are identified as peacocks, while the remaining soluti...
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ISBN:
(纸本)9781728121536
The paper proposes a novel nature-inspired swarm algorithm: peacock algorithm (PA). It is based on the lekking and mating behavior of peacocks. The best solutions are identified as peacocks, while the remaining solutions are called peahens. The peahens are assigned to the peacocks based on their relative positions. peacocks perform exploitation while peahens perform both, exploration as well as exploitation. A peahen explores the search space and moves towards the lek peacock. Once it is near, it may to choose to mate (exploitation) or pursue another peacock (exploration). Every peacock moves towards the dominant peacock (best solution) to enhance its mating chances. The dominant peacock maintains his lek by pushing away other peacocks if they encroach upon its lekking area. The algorithm maintains diversity by adding random solutions whenever two solutions are found to be similar. To test the efficiency of the proposed work, it is compared over a set of 23 benchmark functions to nine other algorithms, which are a mixture of well-established and new algorithms. Its performance is also compared over the CEC'14 test suite to six algorithms. Experimental results demonstrate the superiority of PA, establishing it as a promising novel algorithm.
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