多目标优化的生长竞争蚁群算法

Growing Competitive Ant Algorithm for Multi-objective Optimization

提出一种求解多目标优化的生长竞争蚁群算法。该方法将生长竞争规则引入蚁群算法,给出了在连续空间多目标函数优化的算法描述,定义了生长竞争规则及蚁群邻域的转移概率,并提出了实现算法的具体步骤。算法在MATLAB环境下,对一些典型的测试函数进行了求解和验证,实验结果表明该方法具有向真实的Pareto前沿逼近的效果,是一种求解多目标优化的有效方法。

A growing competitive ant algorithm for solving multi-objective function optimization is presented.The proposed algorithm introduces the rule of growing competition into the ant algorithm and gives a growing competitive ant algorithm with its mathematical description that can be used for solving the multiobjective function optimization problem of continuous systems.The rule of growing competitive and the transition probability are described.The algorithm is coded in MATLAB,and is tested through series of typical problem instances.The simulation results show that the algorithm can efficiently reach the true Pareto frontier.