Strategies in Hybrid Evolutionary Algorithms for Optimization
Evolutionary computing has grown to be a significant methodology in the field of research. Robustness and adaptation are some of the prime features of evolutionary algorithms as compared to other global optimization techniques. Even though evolutionary computation is popularly used for solving several important practical problems in engineering, business, commerce, etc., there is scope for fine-tuning its performance. It is not easy to find any one best algorithm for solving all optimization problems. Hence there is need for a hybrid algorithm which is capable of handling several real world challenges such as, noise, imprecision and uncertainty. This paper presents a review on the methodologies adopted for hybrid evolutionary Algorithms.
Keywords: Evolutionary algorithms, genetic algorithm, particle swarm optimization, ant colony optimization, bacterial foraging optimization
Cite this Article
Vishal Jain, Devender Saini, Saloni. Strategies in Hybrid Evolutionary Algorithms for Optimization. Journal of Advancements in Robotics. 2017; 4(3): 29–32p.
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