Bespoke Artificial Bee Colony Algorithm to Determine the Earthquake locations

Divya Prakash


Metaheuristic algorithms are achieving a great success and gaining the attention of many researchers, to solve or optimize real world problems. In the present study we focus on recently proposed metaheuristic that mimics the foraging behaviour of honeybees called artificial bee colony algorithm (ABC). ABC consist of three groups of bees namely employed, onlooker and scout bees. Likewise other metaheuristic algorithms ABC is good in exploration while poor in exploitation while foraging for food source. A poor balance between exploration and exploitation may result in a weak optimization method which may cause premature convergence, trapping in a local optima, and stagnation. In this paper we tried to improve the exploitation capability which in turn accelerates the convergence of ABC by modifying the onlooker bee phase. The modified variant called BABC is applied to determine the seismic location in the Earth’s crust and upper mantle.


Metaheuristic; Artificial Bee Colony; Exploitation; Convergence; Earthquake; Hypocenter

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