• 前沿与综合应用 •

### 基于博弈论的散货港口堆场堆位分配算法

1. 1. 武汉理工大学 计算机科学与技术学院, 武汉 430063;
2. 交通物联网技术湖北省重点实验室(武汉理工大学), 武汉 430070
• 收稿日期:2020-06-28 修回日期:2020-10-20 出版日期:2021-03-10 发布日期:2021-03-15
• 通讯作者: 李勇华
• 作者简介:张舒瑶(1997-),女,浙江平阳人,硕士研究生,主要研究方向:博弈论、港口调度算法;李勇华(1977-),男,湖北武汉人,副教授,博士,主要研究方向:博弈论、港口调度算法;范家佳(1994-),男,重庆人,硕士研究生,主要研究方向:调度优化、博弈论。
• 基金资助:
中央高校基本科研业务费专项资金资助项目（2019Ⅲ137CG）；内河航运技术湖北省重点实验室基金资助项目（NHHY2017003）；交通物联网技术湖北省重点实验室基金资助项目（2017III028-002）。

### Bulk storage assignment algorithm in bulk port based on game theory

ZHANG Shuyao1,2, LI Yonghua1,2, FAN Jiajia1,2

1. 1. School of Computer Science and Technology, Wuhan University of Technology, Wuhan Hubei 430063, China;
2. Hubei Key Laboratory of Transportation Internet of Things(Wuhan University of Technology), Wuhan Hubei 430070, China
• Received:2020-06-28 Revised:2020-10-20 Online:2021-03-10 Published:2021-03-15
• Supported by:
This work is partially supported by the Fundamental Research Fund for the Central Universities (2019Ⅲ137CG), the Fund of Hubei Key Laboratory of Inland Shipping Technology (NHHY2017003), the Fund of Hubei Key Laboratory of Transportation Internet of Things (2017III028-002).

Abstract: The bulk port has a limited storage yard, during the entering port operation of cargos, there is the problem that how to give consideration to both the operating efficiency and arranging the reasonable storage of cargos in the storage yard with dynamic changes of cargos entering and leaving the port. In order to solve the problem, a Bulk Storage Assignment Algorithm in Bulk port based on Game theory (BSAABG) was proposed. Firstly, the storage assignment behavior was modelled as a dynamic game, and the satisfaction equilibrium was applied to analyze this game. Assuming that each batch of cargos has an expectation for assignment benefit, the game will reach satisfaction equilibrium when all cargos meet their expectations. Then, BSAABG was used to solve the model constructed above, and the convergence of the proposed algorithm was proved theoretically. Experimental results show that, when the number of cargo batches is 20, BSAABG can increase the average cargo satisfaction by 62.5% and 18.2% compared to the manual assignment method (simulated by Greedy Algorithm (GA)) and Storage Assignment algorithm Based on Rule (SABR) respectively, and has the storage assignment benefit 6.83 times and 3.22 times of those of GA and SABR respectively. It can be seen that the proposed algorithm can effectively improve the average cargo satisfaction and the storage assignment benefit.