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期刊信息
  • 主管单位:
  • 上海市教育委员会
  • 主办单位:
  • 上海理工大学
  • 主    编:
  • 庄松林
  • 地    址:
  • 上海市军工路516号
  • 邮政编码:
  • 200093
  • 联系电话:
  • 021-55277251
  • 电子邮件:
  • xbzrb@usst.edu.cn
  • 国际标准刊号:
  • 1007-6735
  • 国内统一刊号:
  • 31-1739/T
  • 邮发代号:
  • 4-401
  • 单    价:
  • 15.00
  • 定    价:
  • 90.00
符俊波,马慧民,张爽,雷悦.有垃圾量变动的生活垃圾收运车辆调度干扰管理研究[J].上海理工大学学报,2017,(4):368-375.
有垃圾量变动的生活垃圾收运车辆调度干扰管理研究
Disruption Management of Garbage Collection and Transportation Vehicle Routing Under the Changing of Garbage Amount
投稿时间:2017-03-06  
DOI:10.13255/j.cnki.jusst.2017.04.011
中文关键词:  生活垃圾  车辆调度  垃圾量变动  干扰管理  遗传算法
英文关键词:garbage  vehicle routing  garbage amount change  disruption management  genetic algorithm
基金项目:教育部人文社会科学研究青年基金资助项目(15YJC630089)
作者单位E-mail
符俊波 上海理工大学 管理学院, 上海 200093  
马慧民 上海电机学院 商学院, 上海 201306 mahm81@163.com 
张爽 上海理工大学 管理学院, 上海 200093  
雷悦 上海电机学院 商学院, 上海 201306  
摘要点击次数: 119
全文下载次数: 114
中文摘要:
      为解决由垃圾收集点垃圾量变化引发的生活垃圾收运车辆调度干扰问题,提出基于干扰管理思想的扰动恢复策略和方案.通过分析干扰事件对垃圾收运系统的扰动,构建垃圾收运车辆调度的扰动辨识和扰动度量,并以新方案与原方案偏差最小为目标,建立扰动恢复数学模型.设计基于车辆收运路径编码方式的遗传算法,求解该类问题.为统一车辆收运状态,引入虚拟收集点概念,并对干扰管理目标函数中的惩罚参数进行研究.最后,通过实例进行仿真实验,并与重调度结果进行比较,验证干扰管理模型和遗传算法的有效性.研究结果表明,干扰管理可以有效降低计划偏离度,并合理控制成本.
英文摘要:
      To deal with the disruption on the garbage collection and transportation vehicle routing caused by the changing of garbage amount at garbage collection point,disruption recovery strategies and solutions were put forward based on the disruption management theory.By analyzing the influence of interference events on the waste collection and transportation system,the disturbance identification and disturbance measurement of vehicle routing were studied,and a mathematical disruption recovery model was established aiming at minimizing the deviation from the original plan.A genetic algorithm based on the vehicle collection and transportation route encoding was designed to solve the problem.In order to unify the vehicle collection and transportation state,the concept of virtual collection point was introduced,and the penalty parameter in disruption management plan was studied.In the end,through simulation experiments and comparing with the rescheduling results,the effectiveness of the disruption management model and genetic algorithm was verified.The results show that the disruption management can reduce the plan deviation effectively,and control the cost reasonably.
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