一个基于Stackelberg游戏的港口拖船调度多目标模糊编程模型
Yangjun Ren1, Qiong Chen2, Yui-Yip Lau3
1School of Economics and Trade, Changzhou Vocational Institute of Textile and Garment, Changzhou, 213164, China.
Scientific reports
|October 24, 2024
概括
这项研究优化了拖船在不确定的港口环境中的调度,使用斯塔克尔伯格游戏模糊模型和一种新的海优化算法. 该方法平衡了燃料效率,任务缓冲和动态操作的完成时间.
科学领域:
- 运营研究 运营研究
- 海上物流的海上物流
- 优化理论 优化理论
背景情况:
- 港口运营面临着动态任务到达和不确定的拖船运行时间的挑战.
- 有效的拖船调度对于最小化成本和最大化海上物流效率至关重要.
研究的目的:
- 开发一个优化模型,考虑拖船调度的动态任务和模糊的操作时间.
- 调查拖船运营商和港口调度员在调度中的决策影响.
- 为了尽量减少燃料消耗和完成时间,同时最大限度地提高缓冲时间.
主要方法:
- 基于Stackelberg游戏的模糊模型被提出,拖船运营商和港口调度员作为决策者.
- 开发了一个海优化算法 (SOA),结合优先编码和遗传操作员.
- 拟议的SOA与CPLEX,遗传算法和模拟化使用45个问题案例进行了基准测试.
主要成果:
- 拟议的SOA在解决港口拖船调度问题方面表现出卓越的效率.
- 模糊编程模型的实用性通过对公平性和不确定性参数的实验来验证.
- 分析包括调整不确定的参数的信心水平从0%到100%.
结论:
- 开发的海优化算法对于复杂的港口拖船调度是有效的.
- 模糊模型为管理海上运营中的不确定性提供了一个实际的框架.
- 优化日程安排提高了港口物流的运营效率,成本效益和公平性.
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