Research on Optimal Control and Decision of Autonomous Vehicle Storage and Retrieval System

由于目前AS/RS系统的巷道易陷入瘫痪，导致货物无法进行存取，严重影响自动化立体仓库存取系统的柔性。随着自动化立体仓库不断朝着自动化、集成化、信息化、智能化方向发展，目前出现了一种新型的自动化立体仓库货物存取系统—自动小车存取系统（AutonomousVehicleStorageandRetrievalSystem，AVS/RS），它主要包括轨道导引小车系统（RailGuidedVehiclesSystem，RGVS）、升降机系统和货架以及货物缓存区。对于该系统的研究主要还处于静态模型阶段，为了进一步推广AVS/RS的应用，研究其优化控制技术等系统动态问题是非常迫切的。因此本文以自动小车存取系...The AS/RS easily falls into entire roadway paralysis when one of the stackers goes wrong in the process of operation. Goods in the related ware location with the roadway can’t be storage and retrieval, which seriously affects the flexibility of the system. With the development of warehouse towards automation, integration, information and intelligent , a new styp of storage/retrieval(R/S) system ...学位：工学博士院系专业：信息科学与技术学院自动化系_系统工程学号：2322007015400

Modeling and optimization of RGV system based on improved QPSO

为提高自动小车存取系统中轨道导引小车系统的出入库作业效率,提出了一种基于改进量子微粒群的优化方法。分析了轨道导引小车系统出入库作业任务队列特征,建立了数学模型。在此基础上利用量子微粒群算法进行优化调度,并在该算法中引入高斯变异算子,克服了其容易陷入局部最优的缺点。通过仿真实验表明了方法的可行性和有效性。To improve the performance of Rail-Guided Vehicles System(RGVS) in Automatic Vehicle Storage and Retrieval Systems(AVS/RS),an optimization method based on improved Quantum Particle Swarm Optimization(QPSO) was proposed.Firstly,sequencing characteristics of tasks in RGVS were analyzed,and a mathematical model was established.Then,a QPSO algorithm was proposed to solve the scheduling problem.Meanwhile,the Gaussian mutation operator was introduced into this algorithm to overcome its shortcoming of falling into local convergence.Finally,feasibility and effectiveness of the presented method was shown by experimental results.国家自然科学基金资助项目(60975052);厦门大学国家“211三期工程建设”资助项目(0630-E62000)---