Real-time Planning and Optimization under Uncertainty in Logistics and Transportation

物流运输不确定性下的实时规划与优化

• 批准号: RGPIN-2017-05224
• 负责人: Jena, SanjayDominik
• 金额: $ 1.46万
• 依托单位: Université du Québec à Montréal
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=636749
• 关键词: Real; time; Planning; Optimization; under

Logistics and transportation related operations typically account for large parts of total project costs and are linked to major pollution emission. Both private and public sectors call for more efficiency and reduction of transportation to relieve traffic and pollution emission. While mathematical optimization has been among the most successful tools to provide efficient planning solutions for these domains, models have been traditionally based on forecasts of the problems’ parameters. The ongoing increase of information technology capacity to capture and store data from different sources offer an opportunity to the Operations Research community to improve the performance of produced planning solutions in practice.

物流和运输相关业务通常占项目总成本的很大一部分，并与主要污染排放有关。私营和公共部门都呼吁提高效率和减少运输，以缓解交通和污染排放。虽然数学优化是为这些领域提供有效规划解决方案的最成功的工具之一，但模型传统上是基于对问题参数的预测。不断增加的信息技术能力，以捕捉和存储来自不同来源的数据提供了一个机会，业务研究界，以提高在实践中产生的规划解决方案的性能。