Multi-year planning for optimal navigation channel dredging and dredged material management

被引:8
作者
Bian, Zheyong [1 ,2 ]
Bai, Yun [2 ,3 ]
Douglas, W. Scott [4 ]
Maher, Ali [2 ,3 ]
Liu, Xiang [2 ,3 ]
机构
[1] Univ Houston, Coll Technol, Dept Construct Management, 4730 Calhoun Rd, Houston, TX 77004 USA
[2] Rutgers State Univ, Ctr Adv Infrastruct & Transportat, 100 Brett Rd, Piscataway, NJ 08854 USA
[3] Rutgers State Univ, Dept Civil & Environm Engn, 500 Bartholomew Rd, Piscataway, NJ 08854 USA
[4] New Jersey Dept Transportat, Off Maritime Resources, Trenton, NJ 08625 USA
关键词
Maritime infrastructure asset management; Navigation channel maintenance dredging; Dredged material management; Multi -year waterway maintenance planning; Dredging project prioritization and; optimization; Sediment disposal assignment and logistics; ROAD MAINTENANCE OPTIMIZATION; TRANSPORTATION; PROJECTS; SIMULATION; MODEL;
D O I
10.1016/j.tre.2022.102618
中图分类号
F [经济];
学科分类号
02 ;
摘要
Navigation channels are critical maritime infrastructure that supports economic and recreational activities and intermodal freight supply chains, impacting broad areas of the hinterland. Maintenance of the maritime infrastructure is vital to the operations of the transportation system. This paper studies a strategic-level maritime infrastructure asset management problem: multi-year planning of navigation channel maintenance dredging and dredged material management. A mathematical model called dredging planning optimization model (DPOM) is developed to optimize channel dredging planning and dredged material management in confined disposal facilities (CDFs), accounting for practical constraints and considerations, including channel linkage and dependency, channel bundling, CDF accessibility and capacity, shoaling and navigability deterioration over time, reimbursable costs, channel economic values, etc. The problem is formulated as a mixed integer nonlinear programming (MINLP) model, with the objective of maximizing the total economic-value-weighted average navigability under fixed budget. The model can be reformulated as an equivalent mixed integer programming (MIP) model, which can be solved by the CPLEX solver, using the branch and bound algorithm. A heuristic algorithm called the dynamic planning prioritization (DPP) algorithm, is proposed in order to solve largescale problems due to the computational complexity. DPP incorporates a dynamic ranking criterion to overcome the challenge of simultaneously handling all of the practical constraints and considerations, as well as the impact of channel prioritization on future year decisions. Finally, a real-world case study is proposed to illustrate the model results and demonstrate the effectiveness of the MIP model and the DPP algorithm.
引用
收藏
页数:25
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