A Simulation Optimization Approach to Optimize Dredger Fleet Schedule Plan for Dredging Works in Existing Ports

被引:1
|
作者
Tang, Guolei [1 ]
Zhao, Zhuoyao [1 ]
Cao, Lele [2 ]
Qi, Yue [3 ]
Yu, Xuhui [4 ]
Liu, Wenjing [1 ]
机构
[1] Dalian Univ Technol, Fac Infrastruct Engn, State Key Lab Coastal & Offshore Engn, Dalian 116023, Liaoning, Peoples R China
[2] China Design Grp Co Ltd, Ziyun St 9, Nanjing 210000, Jiangsu, Peoples R China
[3] Ministr Transport Peoples Republ China, Transport Planning & Res Inst, Beijing 100000, Peoples R China
[4] Dalian Maritime Univ, Coll Transportat Engn, Dalian 116023, Liaoning, Peoples R China
基金
国家高技术研究发展计划(863计划);
关键词
Simulation optimization (SO); Dredger fleet scheduling (DFS); Uncertainty; Traffic flow;
D O I
10.1061/JCEMD4.COENG-12396
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Making an optimal dredger fleet scheduling (DFS) plan is difficult for dredging works in existing ports, where the dredging activities are interrupted by stochastic vessel traffic. Therefore, a simulation optimization (SO) approach is adopted to solve the DFS problem. In the SO approach, an agent-based simulation model is first developed to simulate the stochastic traffic flow and possible spatiotemporal traffic conflicts between vessels and dredgers. Then, this simulation model is integrated with an optimization model to find the optimal DFS plan with the objective of minimum total dredging equipment usage fees. Finally, the proposed SO approach is applied to a 4-dredging-job dredging work. The results demonstrate its applicability in identifying the bottlenecks of the DFS plan and finding the optimal DFS plan. This research contributes to gaining more insights into using the SO approach to provide decision making for dredging work planning under uncertainty.
引用
收藏
页数:14
相关论文
共 26 条
  • [21] Train schedule optimization in a high-speed railway system using a hybrid simulation and meta-model approach
    Hassannayebi, Erfan
    Boroun, Morteza
    Jordehi, Shafagh Alaei
    Kor, Hamrah
    COMPUTERS & INDUSTRIAL ENGINEERING, 2019, 138
  • [22] OPTIMIZATION OF CLINICAL DOSE SCHEDULE TO MANAGE NEUTROPENIA: LEARNINGS FROM A SEMI-MECHANISTIC MODELING SIMULATION APPROACH.
    Guo, Y.
    Haddish-Berhane, N.
    Xie, H.
    Ouellet, D.
    CLINICAL PHARMACOLOGY & THERAPEUTICS, 2019, 105 : S97 - S97
  • [23] OPTIMIZATION OF CLINICAL DOSE SCHEDULE TO MANAGE NEUTROPENIA: LEARNINGS FROM A SEMI-MECHANISTIC MODELING SIMULATION APPROACH.
    Guo, Y.
    Haddish-Berhane, N.
    Xie, H.
    Ouellet, D.
    CLINICAL PHARMACOLOGY & THERAPEUTICS, 2019, 105 : S40 - S40
  • [24] A sustainable water-food-energy plan to confront climatic and socioeconomic changes using simulation-optimization approach
    Zeng, X. T.
    Zhang, J. L.
    Yu, L.
    Zhu, J. X.
    Li, Z.
    Tang, L.
    APPLIED ENERGY, 2019, 236 : 743 - 759
  • [25] A new approach to integrate GPU-based Monte Carlo simulation into inverse treatment plan optimization for proton therapy
    Li, Yongbao
    Tian, Zhen
    Song, Ting
    Wu, Zhaoxia
    Liu, Yaqiang
    Jiang, Steve
    Jia, Xun
    PHYSICS IN MEDICINE AND BIOLOGY, 2017, 62 (01): : 289 - 305
  • [26] Joint Scheduling of Yard Crane, Yard Truck, and Quay Crane for Container Terminal Considering Vessel Stowage Plan: An Integrated Simulation-Based Optimization Approach
    Hsu, Hsien-Pin
    Wang, Chia-Nan
    Fu, Hsin-Pin
    Dang, Thanh-Tuan
    MATHEMATICS, 2021, 9 (18)