An efficient ant colony optimization for real parameter optimization

This paper presents an ant colony optimization based algorithm to solve real parameter optimization problems. In the proposed method, an operation similar to the crossover of the genetic algorithm is introduced into the ant colony optimization. The crossover operation with Laplace distribution following a few promising descent directions (FPDD-LX) is proposed to be performed on the pheromone of the ant colony. The proposed algorithm is compared with other existing works on some benchmark functions. The simulation results show that the proposed method outperforms other algorithms for the real parameter optimization.

[1]  R. Storn,et al.  Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series) , 2005 .

[2]  Nicolas Monmarché,et al.  On how Pachycondyla apicalis ants suggest a new search algorithm , 2000, Future Gener. Comput. Syst..

[3]  Cui Zhang,et al.  An Effective Ant Colony Algorithm for Graph Planarization Problem , 2011, ICIC.

[4]  M. Yamamura,et al.  Multi-parent recombination with simplex crossover in real coded genetic algorithms , 1999 .

[5]  Abbas Afshar,et al.  Ant Colony Optimization for Continuous Domains: Application to Reservoir Operation Problems , 2008, 2008 Eighth International Conference on Hybrid Intelligent Systems.

[6]  Zhiqiang Chen,et al.  An efficient real-coded genetic algorithm for real-parameter optimization , 2010, 2010 Sixth International Conference on Natural Computation.

[7]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[8]  Alden H. Wright,et al.  Genetic Algorithms for Real Parameter Optimization , 1990, FOGA.

[9]  Ian C. Parmee,et al.  The Ant Colony Metaphor for Searching Continuous Design Spaces , 1995, Evolutionary Computing, AISB Workshop.

[10]  P. N. Suganthan,et al.  Differential Evolution Algorithm With Strategy Adaptation for Global Numerical Optimization , 2009, IEEE Transactions on Evolutionary Computation.

[11]  Zhiqiang Chen,et al.  A New Framework with FDPP-LX Crossover for Real-Coded Genetic Algorithm , 2011, IEICE Trans. Fundam. Electron. Commun. Comput. Sci..

[12]  Johann Dréo,et al.  A New Ant Colony Algorithm Using the Heterarchical Concept Aimed at Optimization of Multiminima Continuous Functions , 2002, Ant Algorithms.

[13]  Krzysztof Socha,et al.  ACO for Continuous and Mixed-Variable Optimization , 2004, ANTS Workshop.

[14]  Kusum Deep,et al.  A new crossover operator for real coded genetic algorithms , 2007, Appl. Math. Comput..

[15]  Isao Ono,et al.  A Real Coded Genetic Algorithm for Function Optimization Using Unimodal Normal Distributed Crossover , 1997, ICGA.