Abstract: Aiming at the horizontal transportation scheduling problem of Automatic Guided Vehicle (AGV) in an automated terminal,the container task assignment and AGV path planning were considered and mapped to parallel machine scheduling problems.A mathematical programming model for horizontal transportation scheduling of automated terminals was established to minimize the time of horizontal transportation.To improve the solution quality,an improved artificial bee colony algorithm was developed,which improved the neighborhood search performance of individual bees and introduced a population size adaptive mechanism to change the population size according to the abundance of food sources.Based on the actual data of Yangshan Phase IV Automated Container Terminal,numerical experiments were conducted between the improved algorithm and multiple intelligence algorithms,which proved the superiority and effectiveness of the proposed algorithm.The proposed algorithm could shorten the transportation time and provide decision support for the automated container terminal.

Key words: automated container terminal, automated guided vehicle, parallel machine scheduling, improved artificial bee colony algorithm

摘要： 针对实际场景下自动化码头中自动导引车（AGV）的水平运输调度问题,考虑集装箱任务指派和AGV路径规划并将其映射为并行机调度问题,以最小化水平运输耗时为优化目标,构建了自动化码头的水平运输调度数学规划模型。为提高求解质量,开发了一种改进人工蜂群算法。该方法提高了蜂群个体的邻域搜索性能,并引入种群规模自适应机制,根据食物源丰富与否改变种群规模。最后,根据洋山四期自动化码头的历史运营数据设计了不同规模的算例,并将改进算法与多种智能算法及其改进算法进行了对比测试,从而证明了所提算法的优越性和有效性,同时表明开发的算法能够缩短水平运输耗时,为自动化码头提供决策支持。

关键词: 自动化码头, 自动导引车, 并行机, 改进人工蜂群算法