基于混合遗传算法的混堆箱区内场桥调度研究

Yard Crane Scheduling in the Mixture Storage Block Based on Hybrid Genetic Algorithm

所谓混堆模式下集装箱箱区内场桥调度问题,是指在固定时段内,将有限的场桥资源在混堆模式集装箱港口堆场的单个箱区内进行分配和排序,以最大限度地减少该时段内所有任务的等待成本和场桥非装卸成本为目标,并保证不能超过场桥的作业强度极限.在充分考虑了多场桥作业时须有安全距离和不能相互跨越,以及内外集卡的优先级有差异和集卡等待时间有上限等现实约束下,对此问题构建了非线性数学规划模型.基于问题自身的特点设计了基于任务排序的染色体结构,用融入禁忌搜索的混合遗传算法进行求解.最后通过实例分析证明了模型和算法的有效性.

The yard crane scheduling problem in the mixture storage container terminal＇s block involves the allocation of limited yard crane resource and the scheduling of loading and unloading tasks on each block in the mixture storage container terminal, in order to reduce the waiting cost of all tasks and the non-load and non-unload cost of all operating yard cranes during the fixed span, as well as assure those operating yard crane＇s operation strength not passing the strength limit. Under the real constraints of non-crossing of yard cranes and keeping safe distance when multi-yard cranes are working together, along with different priority level between the inner truck and outer truck, and those trucks＇ waiting time limit, the non-linear mathematical planning model is set up. A hybrid genetic algorithm （HGA） is proposed according to the characteristics of the problem which is based on the tabu search algorithm, and the chromosome representation is structured on the sequence of tasks. Finally, the model and the algorithm are proved by one real example.