Advanced data-driven optimization tools for public transit scheduling and parcel delivery
Advanced data-driven optimization tools for public transit scheduling and parcel delivery
批准号:
520349-2017
负责人:
Desaulniers, Guy
金额:
$6.72万
依托单位国家:
加拿大
项目类别:
Collaborative Research and Development Grants
财政年份:
2019
资助国家:
加拿大
项目状态:
已结题
起止时间:
2019-01-01 至 2020-12-31
中文摘要
GIRO Inc.是开发和商业化基于优化的软件的全球领导者,用于规划公共交通和邮政公司的运营。该研究项目旨在为GIRO的Hastus和GeoRoute软件开发新的数据驱动优化算法,分别用于公共交通和邮政公司。一些研究结果将适用于其他情况。对于公共交通公司,我们建议针对两个问题开发最先进的解决算法:包含行程变化的综合公交和值班调度问题,允许稍微改变某些公交行程的时间表;以及需要规划电池充电的电动公交车调度。在邮政公司,我们观察到随着电子商务的出现,要投递的包裹数量有所增加。邮差被分配到紧凑的地区,这些地区之间的平均工作量必须尽可能平衡。在这个项目中,我们将设想一种算法,当某些邮递员超载时,在给定的一天重新平衡工作负载。作为通用开发,我们计划通过将机器学习(人工智能)工具集成到GIRO软件和许多其他公司中来改进其使用的优化算法。这些工具将利用通过移动传感器等方式获得的大量数据。这项研究将给加拿大带来若干好处。首先,加拿大私有公司GIRO将改进其在全球商业化的两款软件。其次,加拿大邮政和几家加拿大公共交通公司计划与GeoRoute或Hastus合作,他们将获得改进的算法,这将有助于他们实现节省。最后,将培训五名研究生和两名博士后,他们的专业经常在蒙特利尔和加拿大其他地方的优化公司中寻求。
英文摘要
GIRO Inc. is a world leader in the development and commercialization of optimization-based softwares for planning the operations of public transit and postal companies. This research project aims at developing new data-driven optimization algorithms for GIRO's Hastus and GeoRoute softwares dedicated to public transport and postal companies, respectively. Some of the research results will be applicable to other contexts. For public transit companies, we propose to develop state-of-the-art solution algorithms for two problems: Integrated bus and duty scheduling problem with trip shifting that allows to slightly change the schedule of certain bus trip; and Electric bus scheduling which requires planning battery recharges. In postal companies, we observe an increase in the number of parcels to deliver with the advent of e-commerce. The postmen are assigned to compact territories and the average workload must be balanced as much as possible between these territories. In this project, we will conceive an algorithm to rebalance the workloads on a given day when some postmen are overloaded. As generic developments, we plan to improve the optimization algorithms used in GIRO's softwares and in many other companies by integrating machine learning (artificial intelligence) tools into them. These tools will exploit a huge amount of data that have become available via, e.g., mobile sensors. This research will yield several benefits to Canada. First, a Canadian-owned private company, GIRO, will enhance two of its softwares that are commercialized worldwide. Second, Canada Post and several Canadian public transport companies that plan their operations with either GeoRoute or Hastus will have access to improved algorithms that will help them realized savings. Finally, five graduate students and two postdoctoral fellows whose specialization is often sought in optimization-based companies in Montreal and elsewhere in Canada will be trained.
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