Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Aerodynamic efficiency of intermodal freight trains can be significantly improved by minimizing the adjusted gap lengths beten adjacent loads.  first develops a static model to optimize load placement on a sequence of intermodal trains that have scheduled departure times. This model applies when full information on all trains and loads is available. Then,  develop a dynamic model to account for the more realistic situation in which there is incomplete or uncertain information on future trains and incoming loads.  develops methodology to balance beten (i) the advantage from optimizing multiple trains together and (ii) the risk of making suboptimal decisions due to incomplete future information.  propose a rolling horizon scheme to address this challenge, where exponentially decreasing ights are assigned to the objective functions of future trains. Numerical results based on empirical data show significant aerodynamic efficiency benefits from these optimization models.
['Yung Cheng Lai', 'Yanfeng Ouyang', 'Christopher P L Barkan']
I am writing a research paper on a idea A Rolling Horizon Model to Optimize Aerodynamic Efficiency of Intermodal Freight Trains with Uncertainty
[{"from": "human", "value": "I am writing a research paper on a idea A Rolling Horizon Model to Optimize Aerodynamic Efficiency of Intermodal Freight Trains with Uncertainty"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Aerodynamic efficiency of intermodal freight trains can be significantly improved by minimizing the adjusted gap lengths beten adjacent loads.  first develops a static model to optimize load placement on a sequence of intermodal trains that have scheduled departure times. This model applies when full information on all trains and loads is available. Then,  develop a dynamic model to account for the more realistic situation in which there is incomplete or uncertain information on future trains and incoming loads.  develops methodology to balance beten (i) the advantage from optimizing multiple trains together and (ii) the risk of making suboptimal decisions due to incomplete future information.  propose a rolling horizon scheme to address this challenge, where exponentially decreasing ights are assigned to the objective functions of future trains. Numerical results based on empirical data show significant aerodynamic efficiency benefits from these optimization models."}]