基于多Agent的偏好泊位约束下泊位-岸桥分配

Berth-Crane Allocation Problem Based on Multi-Agent with the Preferences of Berthing Position

泊位和岸桥是码头前沿最宝贵的资源,为其设计合理调度机制能够获得更高的效能。考虑连续泊位的岸线,加入偏好泊位约束条件,以最小化偏离偏好泊位成本为目标函数,结合多Agent的智能化特点,提出基于多Agent的联合调度模型,在模型基础上设计分步的遗传算法,实现高效的泊位岸桥联合调度。并用实验证明模型和算法的有效性,实验结果验证引入偏好泊位约束条件确实能提高码头作业效率,降低因偏离偏好泊位带来的成本。

Berth and crane are the most precious resources, making reasonable design for the scheduling mechanism can make full use of resources.Considers the continuous berth with preference berthing constraints, to minimize the deviation from the berth preference cost as objective function, combined with the Multi-Agent＇s intelligent characteristics, proposes a scheduling model based on Multi-Agent. Designs a new genetic algorithm bases on the model to achieve efficient berth crane scheduling. And makes example to prove the validity of the model and algorithm. The experimental results verify the introduction of preference constraints can efficiency improve the berth handling, and also can reduce the cost caused by the deviation from the berth preference.