Investigating Freight Uncertainties to Improve Truckload Operational Efficiency**

该项目解决了货运不确定性，这是货运县集团(行业合作伙伴)在日常运营中面临的主要问题之一。由于客户可以选择在服务开始前重新安排或取消他们的请求，因此运费存在不确定性。这些最后一刻的变化对公司的运营业绩产生了巨大的负面影响，因为它们迫使公司在不同的地点(城市)之间调空卡车。这不仅对公司的经济不利，而且对环境也是有害的，因为它会导致效率低下的卡车移动产生更高的二氧化碳排放量。*该项目的关键创新在于它开发了一种决策机制，该机制考虑了行业合作伙伴运营中现有的货运不确定性。该机制试图利用先进的随机优化算法来研究客户行为中的不确定性(即订单取消或重新调度)。为了建立这样一种机制，货运县集团(一家以资产为基础的航空公司)与其学术伙伴(瑞尔森大学)合作，开始了这一项目的工作。这一结果不仅将为公司带来经济效益，还将通过减少对空气污染的贡献来改善其环境业绩。

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.