Hybrid ant colony optimization algorithms for mixed discrete-continuous optimization problems

作者：Liao T Warren^*; Kuo R J; Hu J T L

来源：Applied Mathematics and Computation, 2012, 219(6): 3241-3252.

DOI：10.1016/j.amc.2012.09.064

• Ant colony optimization
• Metaheuristic
• Hybrid metaheuristic
• Mixed discrete-continuous
• Constrained optimization

This paper presents three new hybrid ant colony optimization algorithms that are extended from the ACO(R) developed by Socha and Dorigo for solving mixed discrete-continuous constrained optimization problems. The first two hybrids, labeled ACO(R)-HJ and ACO(R)-DE, differs in philosophy with the former integrating ACOR with the effective Hooke and Jeeves local search method and the latter a cooperative hybrid between ACO(R) and differentia evolution. The third hybrid, labeled ACO(R)-DE-HJ, is the second cooperative hybrid enhanced with the Hooke and Jeeves local search. All three algorithms incorporate a method to handle mixed discrete-continuous variables and the Deb%26apos;s parameterless penalty method for handling constraints. Fourteen problems selected from various domains were used for testing the performance of both algorithms. It was showed that all three algorithms greatly outperform the original ACO(R) in finding the exact or near global optima. An investigation was also carried out to determine the relative performance of applying local search with a fixed probability or varying probability.

• 出版日期2012-11-25