Dredging projects selection when the random shoaling effect is considered
| 项目名称： | Dredging projects selection when the random shoaling effect is considered |
| 摘要： | Dredging is a constant operation to maintain the waterway shipping capacity along the rivers, coastal lines as well as ports and harbors. The goal is to achieve a maximum network capacity to support the regional and national economies within the range of a given budget. Shoaling happens after dredging to partially offset or undermine the dredging benefits. Wisely spending the dredging budget for a network capacity by considering the shoaling effect is the objective of this proposed research. This proposal assumes shoaling at each location/section follows a known probability distribution with a given draft. It will build on earlier models and algorithms developed by the research team to propose optimality based stochastic model and algorithms for this particular problem, which specially considers interdependency of project effects on the network. This project expects to complement other researchers’ earlier work that adopts discrete scenario based optimization method through simulation. |
| 状态： | Active |
| 资金： | 105000 |
| 资助组织： | Maritime Transportation Research and Education Center<==>Office of the Assistant Secretary for Research and Technology |
| 执行机构： | Texas A&M University, College Station |
| 开始时间： | 20191001 |
| 预计完成日期： | 20211231 |
| 主题领域： | Maintenance and Preservation；Marine Transportation；Planning and Forecasting |
相关文献
- Synthesis of Information Related to Highway Problems. Topic 47-02. Alternate Design/Alternate Bid Process for Pavement Type Selection
- Utv�rdering av m�jligheten att �teranv�nda lera med inneh�ll av kalk och cement
- Impact of Low Shrinkage Mixes on Late-Age Random Cracking in Pavements with Use of Early Entry Sawing
- Review of Freight Investment Decision-Making Proceses in the Public Sector
- Warrants for Roundabouts
- Does Design‐Build Always Expedite Project Delivery: Insights from SCDOT’s Historical Data from the Past Decade
检索历史
应用推荐
