Yard crane scheduling problem in a container terminal considering risk caused by uncertainty

In a container terminal, the arriving times and handling volumes of the vessels are uncertain. The arriving times of the external trucks and the number of containers which are needed to be brought into or retrieved from a container terminal by external trucks within a period are also uncertain. Yard crane (YC) scheduling is under uncertainty. This paper addresses a YC scheduling problem with uncertainty of the task groups' arriving times and handling volumes. We do not only optimize the efficiency of YC operations, but also optimize the extra loss caused by uncertainty for reducing risk of adjusting schedule as the result of the task groups' arriving times and handling volumes deviating from their plan. A mathematical model is proposed for optimizing the total delay to the estimated ending time of all task groups without uncertainty and the extra loss under all uncertain scenarios. Furthermore, a GA-based framework combined with three-stage algorithm is proposed to solve the problem. Finally, the proposed mathematical model and approach are validated by numerical experiments.     

A case based heuristic for container stacking in seaport terminals

In this paper, we suggest a Case Based heuristic for the online container stacking management system in seaport terminals. The main objectives of the system are to determine the exact position of each import container in the storage area and to control container allocation and react to unexpected events and disturbances in an intelligent, self-organizing and real-time manner. First, we propose learning mechanisms and knowledge models for a better management of knowledge related to disturbances and container environment. This system takes into account different types of containers especially the storage of dangerous containers. For assessment of the suggested system, real data are collected from King Abdul Aziz Dammam seaport terminal (Saudi Arabia). The performance of the developed heuristic is assessed with different scenarios and compared to three other stacking strategies studied in the scientific literature. The obtained results are promising and show that the developed CBR (Case Based Reasoning) based heuristic can be efficient or similar problems, i.e. online container staking.     

基于历史数据分析的容器云安全风险评估方法

容器云受到风险攻击会影响运维性能,无法有效保护内部存储的隐私数据安全。为了准确判断风险攻击类型,最大程度保证用户隐私数据安全,提出基于历史数据分析的容器云安全风险评估方法。根据云计算安全标准,对容器云风险等级进行分类;利用粗糙集算法挖掘容器云历史数据中的风险因素,获得风险因素归约集合;根据容器云的运行特点,通过德尔菲方法和决策隶属度矩阵计算安全风险权重。根据各风险间存在关联性,整合整体风险评估值,实现容器云安全风险评估。实验结果表明,该方法可以有效评估容器云安全风险,且评估结果较为准确,为用户保证隐私数据安全提供参考。     

钢材深加工是搞活钢铁企业的一条有效途径

钢铁企业开展钢材深加工,是搞活钢铁企业,提高经济效益不可忽视的一条途径。本文特对钢铁企业内部开展钢材深加工的意义及有利条件进行了概述,重点介绍了稀油密封多边形干式煤气柜、钢质干贷集装箱等钢材深加工产品的可行性,以及对如何搞好钢材深加工工作,提出了几点建议。     

上海青浦夏雨幼儿园

文章通过对青浦区夏雨幼儿园的设计与建造的分析,展现了在特定环境中建筑作为一种特性容器的空间状态。     

集装箱龙门起重机结构系统动态优化设计

分别以集装箱龙门起重机结构系统的质量和动刚度为动态优化目标,采用灵敏度分析方法,运用有限元分析软件ANSYS对其结构系统进行基于动态特性的优化设计优化后,对不同优化目标下的两个方案进行比较,提出一种重量较轻、静动态性能优良的集装箱龙门起重机结构设计方案.     

基于有限元分析的NG3252自卸车货箱改进设计

针对某重型自卸车货箱在使用过程中由于自身刚度不足造成的侧板变形的问题及减重设计的需要,对其进行了改进设计。首先通过运动学仿真获得货箱处于最大受力状态的位置,利用该位置作为边界条件对货箱进行有限元分析,通过提高货箱底架的抗弯刚度减小侧板的倾斜变形。改进后的货箱保持原有的强度同时刚度提高。     

求解强异类集装箱装载问题的混合蚁群算法

针对强异类集装箱装载问题,设计了一种混合蚁群算法。算法中搜索空间分为货物摆放的优先序列和货物摆放的状态两部分;引入体积大的货物优先放入的启发式规则;将蚂蚁搜索得到的序列与历史最优序列进行交叉,取三者最优序列作为该蚂蚁的搜索路径;在更新信息素时,采取两种挥发系数更新信息素以避免信息素过快饱和,同时分析了算法的复杂度。通过三个强异类实例的测试,表明算法得到的装载方案有较高的空间利用率。     

机场货运平台拖车顶升系统液压缸的同步控制

模拟货运平台拖车实际举升过程中的负载工况,提出多缸液压系统的同步控制策略,对举升液压缸采用分组PID控制.对其中的比例调速阀在AMESim环境下建立其模型,并完成了相关参数的优化.仿真结果表明:PID控制能够满足分组控制的精度要求,流量同步控制可以把同步误差控制在0.5 mm范围内,压力和流量同步在缓变负载下能保持优良特性.     

700 MPa级高强集装箱用钢的研制

介绍了屈服强度700 MPa级集装箱用高强钢的成分设计思路和主要的轧制工艺参数,并分析了产品的性能、组织和析出相。试制结果表明:通卷钢板的力学性能均匀,组织由位错密度很高的块状铁素体和少量贝氏体组成,析出相主要为不同形态的铌、钛的碳氮化物,在铁素体中析出的细小的TiC第二相粒子沉淀强化作用更大。