不确定环境下码头堆场设备集成调度优化

发布时间：2018-04-07 14:58

本文选题：不确定因素　切入点：集成调度　出处：《计算机工程与应用》2017年21期

【摘要】：集装箱码头堆场设备调度优化中,对确定条件下的内集卡和场桥的联合调度研究较多,且没有考虑外集卡的随机到达情况。考虑内集卡和场桥作业过程中的不确定性因素,包括:内集卡行驶速度,场桥行走速度和作业时间,并考虑外集卡随机到达堆场对于内集卡调度作业的影响,构建了不确定因素条件下的堆场设备集成调度优化模型,其优化目标是在考虑外集卡随机到达的情况下,最优化堆场设备的作业时间。设计了求解模型的粒子群算法,并比较了一般确定性模型和考虑不确定因素优化模型的结果。算例结果表明,所建立的模型和算法能有效真实地反映不确定因素对集装箱码头堆场设备作业的影响。
[Abstract]:In the optimization of container terminal yard equipment scheduling, there is much research on the joint dispatch of the inner collecting card and the field bridge under certain conditions, and the random arrival of the external gathering card is not considered.Considering the uncertainty factors in the process of internal gathering card and field bridge operation, including: driving speed of inner collecting card, field bridge walking speed and operation time, and considering the influence of random arrival of external collecting card on internal collecting card scheduling operation.In this paper, an integrated scheduling optimization model for yard equipment under uncertain conditions is proposed. The objective of the model is to optimize the operation time of yard equipment considering the random arrival of external cards.Particle swarm optimization (PSO) algorithm is designed to solve the model, and the results of general deterministic model and optimization model with uncertain factors are compared.The simulation results show that the model and algorithm can reflect the effect of uncertainty factors on the operation of container terminal yard equipment effectively and realistically.
【作者单位】：上海电力学院经济与管理学院;
【基金】：中小物流企业信息化方案与决策(No.H2016-029) 国家自然科学基金(No.71171129) 上海市科委科研计划项目(No.12510501600,No.14DZ2280200)
【分类号】：U691.3

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