改进的人工鱼群混合算法在交通分配中的应用

Artificial Fish Swarm Algorithm for Solving Road Network Equilibrium Traffic Assignment Problem

关于交通规划优化过程,针对均衡交通分配问题,采用目前Frank-W olfe算法收敛速度较慢、计算负担较大限制了均衡模型在实际中的应用,提出遗传算法的人工鱼群混合优化算法求解均衡交通分配问题。在人工鱼群混合优化算法中引入遗传算法的交叉和变异操作,实现优化行为的互补,建立遗传算法的人工鱼群混合优化算法求解变量较多,有较好的弹性需求和用户均衡交通分配模型。通过数值仿真,表明混合优化算法比单一的人工鱼群算法求解交通分配问题效果好,混合优化算法可靠、有效。

This paper is proposed to study the equilibrium traffic assignment problem.For the shortcomings of Frank-Wolfe algorithm such as slow convergence speed and heavy calculation burden that causes the equilibrium traffic assignment model cannot be used efficiently in reality,the hybrid optimization algorithm of AFSA based on GA is applied to solve the equilibrium traffic assignment problem.The hybrid optimization algorithm which realizes optimization complementarity after the crossing and mutation operation of GA is being introduced into AFSA is used to solve elastic demand user equilibrium traffic assignment model which has more variables and so much heavier calculation burden.The results of the numerical example are compared by simple AFSA and the hybrid optimization algorithm.The conclusion drawn from the above comparison is that the hybrid optimization algorithm is more reliable and efficient.