计算机科学 ›› 2013, Vol. 40 ›› Issue (5): 233-236.

• 人工智能 • 上一篇    下一篇

基于量子免疫算法的车辆调度问题优化

任伟   

  1. 浙江工业大学特种装备制造与先进加工技术教育部重点实验室 杭州310014
  • 出版日期:2018-11-16 发布日期:2018-11-16
  • 基金资助:
    本文受国家自然科学基金项目(60970021),浙江省高等学校教师专业发展访问学者项目(FX2012107)资助

Optimization Algorithm for Vehicle Scheduling Problem Based on Quantum Immune

REN Wei   

  • Online:2018-11-16 Published:2018-11-16

摘要: 为优化带时间窗的车辆调度计算问题,引入量子进化算法,提出了一种混合量子免疫进化算法。首先对传统量子旋转门进行改进,使个体在进化过程中向全局最优位置靠近,从而避免算法早熟并保持种群多样性。其次在迭代过程中,引入免疫算子,提取优秀基因片段作为疫苗,接种到种群中其他个体,避免算法性能的倒退。最后,针对Solomon标准实例库实例数据进行多算法编码仿真实验,结果表明,所提混合量子免疫进化算法不仅能够有效解决类似问题,而且能够显著加速收敛。

关键词: 车辆调度问题,量子旋转门,免疫算子,量子进化

Abstract: Aiming at the vehicle scheduling problem with time window,a hybrid quantum evolutionary algorithm with immune operator was put forward.The algorithm improves quantum rotating gate,making individual in evolutionary process close to the global optimum position,so as to avoid prematurity and to maintain the diversity of the population.In the iteration process,an immune operator is introduced,and excellent genes fragment is extracted as vaccine which was vaccinated to the other individuals in the population,as to prevent the algorithm retrogression.Finally,the experimental simulations of the standard instances show that the proposed method can not only effectively solve the problem,but also significantly speed up the convergence.

Key words: Vehicle scheduling problem,Quantum rotating gate,Immune operator,Quantum evolutionary algorithm

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