量子遗传算法在公交车辆调度中的应用

发布时间：2018-05-25 08:22

本文选题：公共交通 + 遗传算法　；参考：《实验室研究与探索》2014年12期

【摘要】：针对公交车辆调度的运行环境以及其现状,考虑到信号灯周期对乘客等车时间的影响,同时为了保证公交公司与乘客的两者利益,建立了公交车辆优化调度模型。针对拒绝策略容易产生效率低的问题,采用惩罚策略设计出一种新的适应度函数。基于基本遗传算法存在早熟收敛和易陷入局部最优解等问题,本文采用量子遗传算法来解决组合问题。研究结果表明,该方法能够有效地解决公交车辆运营优化调度的组合问题。
[Abstract]:In view of the running environment and current situation of bus vehicle scheduling, considering the influence of the signal light cycle on the waiting time of passengers, and in order to ensure the interests of both bus companies and passengers, the optimal scheduling model of public transport vehicles is established. In order to solve the problem of low efficiency of rejection strategy, a new fitness function is designed by using penalty strategy. Based on the problem of premature convergence and easy to fall into local optimal solution of basic genetic algorithm, quantum genetic algorithm (QGA) is used to solve the combinatorial problem. The results show that this method can effectively solve the combinatorial problem of bus operation and optimal scheduling.
【作者单位】：南阳师范学院物理与电子工程学院;重庆大学自动化学院;
【基金】：国家自然科学基金资助(61306007) 河南省教育厅科学技术研究重点项目(14B120003) 河南省科技攻关项目(122102210403) 重庆市自然科学基金重点项目(CSTC2012JJ40002) 南阳师范学院科研项目(ZX2014085)
【分类号】：U491.17;TP18

【相似文献】