Self Adaptive Artificial Bee Colony for Global Numerical Optimization
نویسندگان
چکیده
منابع مشابه
Self Adaptive Artificial Bee Colony for Global Numerical Optimization
The ABC algorithm has been used in many practical cases and has demonstrated good convergence rate. It produces the new solution according to the stochastic variance process. In this process, the magnitudes of the perturbation are important since it can affect the new solution. In this paper, we propose a self adaptive artificial bee colony, called self adaptive ABC, for the global numerical op...
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Numerous problems in engineering and science can be converted into optimization problems. Artificial bee colony (ABC) algorithm is a newly developed stochastic optimization algorithm and has been widely used in many areas. However, due to the stochastic characteristics of its solution search equation, the traditional ABC algorithm often suffers from poor exploitation. Aiming at this weakness o...
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artificial bee colony (ABC) is the one of the newest nature inspired heuristics for optimization problem. In order to improve the convergence characteristics and to prevent the ABC to get stuck on local solutions, a differential ABC (DABC) is proposed. The differential operator obeys uniform distribution and creates candidate food position that can fully represent the solution space. So the div...
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Artificial bee colony (ABC) algorithm invented recently by Karaboga is a biological-inspired optimization algorithm, which has been shown to be competitive with some conventional biological-inspired algorithms, such as genetic algorithm (GA), differential evolution (DE) and particle swarm optimization (PSO). However, there is still an insufficiency in ABC algorithm regarding its solution search...
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ژورنال
عنوان ژورنال: IERI Procedia
سال: 2012
ISSN: 2212-6678
DOI: 10.1016/j.ieri.2012.06.011