基于HGA的智能交通调度优化方法研究

Optimization Method of Intelligent Traffic Dispatch System Based on Hybrid Genetic Algorithms

针对公交车辆运营调度的现状和存在的问题,采用免疫遗传算法对公交车辆智能调度进行优化研究.遗传算法的智能化特征能够有效地改善公交车辆运营调度的不足,提高公交车辆的静态调度能力.在此基础上结合生物免疫机制等边缘学科的理论,将免疫算法与遗传算法有机结合,提出一种改进型混合遗传算法,应用于公交调度管理中的优化,并与利用简单遗传算法的计算过程进行仿真和比较.仿真结果表明,该算法简单高效、稳定性好,能够较好地克服传统方法和现有遗传算法的不足,性能得到了显著提高,获得了满意的效果,提高了公交车辆的运营效率.

Considering existed problems of current public traffic vehicles（PTV）,intelligent dispatch problems of static state for PTV are studied and discussed with immune genetic algorithm（IGA）.Making full use of intelligent characteristics of GA,static dispatch of PTV is improved effectively.Based on GA and the study of the immune principles of creature,immune algorithm is melted into GA,and an improved hybrid GA（HGA） is approved.This advanced algorithm-Immune GA（IGA） is applied to solve some optimization problems in the public traffic intelligent dispatch system（PTIDS）.The computing programs applying GA and IGA are simulated and compared.The results show that IGA is simple,efficient and robust.The performance of the static dispatch is greatly improved and the satisfied effect is achieved.Therefore,we can conclude that IGA can overcome the disadvantages of traditional optimization methods and the GA existed.Consequently,rational and practicable optimization method is provided for the dispatch operation of PTV.