GA and ACO-based Hybrid Approach for Continuous Optimization
Zhiqiang Chen, Rong‐Long Wang · 2015
This paper presents an hybrid algorithm based on genetic algorithm and ant colony optimization for continuous optimization, which combines the global exploration ability of the former with the local exploiting ability of the later.The proposed algorithm is evaluated on several benchmark functions.The simulation results show that the proposed algorithm performs quite well and outperforms classical ant colony optimization and genetic algorithm for continuous optimization, which efficiently balances two contradictory aspects of its performance: exploration and exploitation.