Investigating Freight Uncertainties to Improve Truckload Operational Efficiency**

研究货运不确定性以提高卡车装载运营效率**

• 批准号: 536213-2018
• 负责人: Zolfagharinia, Hossein
• 金额: $ 1.82万
• 依托单位: Ryerson University
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=669968
• 关键词: Investigating; Freight; Uncertainties; Improve; Truckload

This project addresses freight uncertainty, one of the major issues that Cargo County Group (the industry partner), is facing in its daily operations. Freight uncertainty exists as clients have the option to reschedule or cancel their requests before the service starts. These last-minute changes negatively impact the company's operational performance significantly as they force the company to move its trucks empty between different locations (cities). This is not only detrimental to the company economically, but it is also harmful to the environment, as it results in higher CO2 emissions from inefficient truck movements.****The key innovation of this project is in its development of a decision-making mechanism that considers the existing freight uncertainty in the industry partner's operations. This mechanism attempts to utilize advanced algorithms of stochastic optimization to investigate the uncertainties in the customers' behavior (i.e., order cancellation or rescheduling). To develop such a mechanism, Cargo County Group (an asset-based carrier) in collaboration with its academic partner (Ryerson University) have started their work on this project. The outcome will not only bring economic benefits to the company, but it will also improve its environmental performance by decreasing its contribution to air pollution.

该项目解决了货运的不确定性，这是Cargo County Group（行业合作伙伴）在日常运营中面临的主要问题之一。运费的不确定性是存在的，因为客户可以选择在服务开始之前重新安排或取消他们的请求。这些最后一刻的变化对公司的运营业绩产生了重大负面影响，因为它们迫使公司在不同地点（城市）之间运送空载卡车。这不仅在经济上对公司不利，而且对环境也有害，因为这会导致低效的卡车运输产生更高的二氧化碳排放。该项目的主要创新之处在于其制定了一个决策机制，该机制考虑到行业合作伙伴业务中现有的货运不确定性。该机制试图利用随机优化的高级算法来调查客户行为中的不确定性（即，订单取消或重新安排）。为了开发这样一个机制，Cargo County Group（一家基于资产的航空公司）与其学术合作伙伴（瑞尔森大学）合作，已经开始了他们在这个项目上的工作。这一结果不仅将为公司带来经济效益，而且还将通过减少对空气污染的贡献来改善其环境绩效。