一种混合优化算法及其收敛性证明

针对改进的混沌优化方法和Alopex算法的特性，将改进的Alopex算法嵌入到改进的混沌优化算法中，提出一种混合优化算法，此算法充分发挥了改进的Alopex算法的快速搜索能力和改进的混沌优化方法细致寻优的特性，提高了算法的收敛速度，避免了优化算法陷入局部最优；同时对改进的混沌优化算法和混合优化算法的收敛性进行了证明，仿真结果表明了算法的有效性。     

基于差分算法的反渗透海水淡化优化调度

以系统运行费用为目标的反渗透海水淡化优化调度是一类带有约束的非线性优化问题。针对这一问题,提出一种改进的差分进化算法。该算法对基本差分进化算法中的变异因子和交叉因子进行改进;定义约束违反度函数,将约束优化问题转化为无约束的优化问题。以24小时为一个周期,通过改进的差分进化算法对系统模型进行优化调度。仿真结果表明,改进的算法可以对机组进行优化操作,有效的降低了系统的生产成本。     

A＊算法改进算法及其应用

路径优化问题是现代生活和工作中的一个重要而复杂的问题,路径优化算法则是解决路径优化问题并推广应用路径优化问题的关键.在回顾Dijkstra算法和A*算法的基础上,提出了A*改进算法,并结合例子对算法求解过程进行说明.最后编程实现了Dijkstra算法、A*算法和A*改进算法,并对运行结果进行比较分析.     

基于Petri网模型的JSP粒子群优化调度

提出一种有效的基于Petri网建模及改进的编码粒子群算法的车间作业调度问题优化算法,分析对比了现有的作业车间调度领域中的基于人工智能的优化算法,对所提出的基于Petri网建模和改进的粒子群算法的优化算法进行了性能分析,并对该算法进行了仿真研究,结果表明该算法是可行、有效的。     

改进蚁群算法求解有时间窗的物流配送路径问题

物流配送车辆路径优化问题已被证明是一个NP难题,很难得到最优解。应用蚁群算法对带时间窗的物流车辆路径优化问题进行了算法设计,建立了车辆路径优化问题的蚁群算法数学模型及解决方案。通过对蚁群算法的分析,提出了改进的蚁群算法,并结合实例对该算法进行测试和分析,检验其有效性,结果表明了改进蚁群算法的可行性,符合实际的需要。     

改进粒子群优化算法求解任务指派问题

任务指派问题是典型NP难题，引入粒子群优化算法对其进行求解。建立了任务指派问题的数学模型，给出了粒子群优化算法求解任务指派问题的具体方案。为提高其优化求解效果，引入变异机制及局部更新机制对粒子群优化算法进行改进。实例及数字仿真验证了改进粒子群优化算法的有效性。     

基于非支配排序的多目标蚁群优化算法

蚁群优化算法是一种受自然界蚂蚁觅食启发而设计的智能优化算法,由于其优异的全局搜索性能,近年来在研究和工程领域都得到了广泛关注。本文针对连续域单目标蚁群优化算法进行改进,对多目标优化问题进行求解。首先分析了现有连续域蚁群算法,发现解集排序方法需要改进以适应多目标优化问题求解。对解存档结构进行改进,将每个解的目标值修改为目标向量。在此基础上,通过引入非支配排序方法,对解集分层;然后在层内通过拥挤度进行排序,实现解集的整体排序。所改进的算法通过仿真实验与NSGA-II算法进行了对比,结果表明算法的求解质量更好,并且单次迭代耗时更短。     

改进粒子群三维空间路径规划研究

将改进粒子群优化算法应用于三维空间路径规划。首先给出三维空间建模方法,其次通过在迭代过程中对算法惯性系数[w]分段设置和对粒子位置进行随机扰动的方式来改进粒子群优化算法,然后对路径陷入障碍物的处理方式进行改进,最后给出了基于改进粒子群优化算法的三维空间路径规划的算法流程。仿真结果表明：改进方式能有效提高粒子群优化算法应用于三维空间路径规划的计算效率和可靠性,合理设置路径节点能有效节约计算资源。     

A*算法改进算法及其应用

路径优化问题是现代生活和工作中的一个重要而复杂的问题,路径优化算法则是解决路径优化问题并推广应用路径优化问题的关键。在回顾Dijkstra算法和A^*算法的基础上,提出了A^*改进算法,并结合例子对算法求解过程进行说明。最后编程实现了Dijkstra算法、A^*算法和A^*改进算法,并对运行结果进行比较分析。     

一种改进的微粒群算法*

通过在微粒群算法中引入排雷策略的思想,对微粒群优化算法进行改进,使微粒群算法能摆脱局部极值点的束缚;另外通过在算法的迭代过程中加入旋转方向法,加快算法的收敛速度,从而形成一种新的改进粒子群算法。通过对三个典型函数进行优化计算,并与其他文献的改进微粒群算法的优化结果进行比较,表明基于排雷策略的改进算法很好地解决了粒子群优化算法早收敛、难以跳出局部极值点和收敛较慢的问题。     

基于有向哈希树的认证跳表算法

作为一种重要的认证数据结构,认证跳表在数据认证机制中有着广泛的应用。由于哈希模式对认证跳表的代价有显著的影响,因此提出哈希模式和数据存储模式分离的思想,设计了一种新的认证哈希模式—有向哈希树,并在其基础上设计了新的认证跳表算法。应用分层数据处理、概率分析等数学方法对所提出算法的代价进行了理论分析,并与已有的认证跳表算法做了性能比较。结果表明,本算法在时间、通信和存储代价方面有了较大的改进。     

Improvement of the evaluation of closed-loop production systems with unreliable machines and finite buffers

A closed-loop production system, or loop, is a system in which a constant amount of material flows through a single fixed cycle of workstations and storage buffers. Manufacturing processes that utilize pallets or fixtures can be viewed as loops. Control policies such as CONWIP and Kanban create conceptual loops. Gershwin and Werner (2007) developed a decomposition algorithm that accurately evaluates Buzacott type closed-loop systems of any size. However there are cases where the evaluated production rate, as a function of some system parameter, is discontinuous. Such a discontinuity may give misleading results for loop system design and optimization method. We present two modifications that improve the algorithm of Gershwin and Werner (2007). Two new special types of two-machine one-buffer building blocks are developed for the decomposition, and analytical solutions for them are found. Numerical experiments are provided to show the improvement of the evaluation accuracy as compared with the existing algorithm. The discontinuity in production rate is greatly diminished with these modifications.     

An algorithm to count the number of repeated patient data entries with B tree

An algorithm to obtain the number of different values that appear a specified number of times in a given data field of a given data file is presented. Basically, a well-known B-tree structure is employed in this study. Some modifications were made to the basic B-tree algorithm. The first step of the modifications is to allow a data item whose values are not necessary distinct from one record to another to be used as a primary key. When a key value is inserted, the number of previous appearances is counted. At the end of all the insertions, the number of key values which are unique in the tree, the number of key values which appear twice, three times, and so forth are obtained. This algorithm is especially powerful for a large size file in disk storage.     

Near-perfect hashing of large word sets

This article presents a procedure for constructing a near-perfect hashing function. The procedure, which is a modification of Cichelli's algorithm, builds the near-perfect hashing function sufficiently fast to allow larger word sets to be used than were previously possible. The improved procedure is the result of examining the original algorithm for the causes of its sluggish performance and then modifying them. In doing so an attempt was made to preserve the basic simplicity of th original algorithm. The improved performance comes at the expense of more storage. The six modifications used to improve performance are explained in detail and experimental results are given for word sets of varying sizes.     

Efficiency enhancement of a process-based rainfall–runoff model using a new modified AdaBoost.RT technique

High-efficiency rainfall–runoff forecast is extremely important for flood disaster warning. Single process-based rainfall–runoff model can hardly capture all the runoff characteristics, especially for flood periods and dry periods. In order to address the issue, an effective multi-model ensemble approach is urgently required. The Adaptive Boosting (AdaBoost) algorithm is one of the most robust ensemble learning methods. However, it has never been utilized for the efficiency improvement of process-based rainfall–runoff models.Therefore AdaBoost.RT (Adaptive Boosting for Regression problems and “T” for a threshold demarcating the correct from the incorrect) algorithm, is innovatively proposed to make an aggregation (AdaBoost-XXT) of a process-based rainfall–runoff model called XXT (a hybrid of TOPMODEL and Xinanjing model). To adapt to hydrologic situation, some modifications were made in AdaBoost.RT. Firstly, weights of wrong predicted examples were made increased rather than unchangeable so that those “hard” samples could be highlighted. Then the stationary threshold to demarcate the correct from the incorrect was replaced with dynamic mean value of absolute errors. In addition, other two minor modifications were also made. Then particle swarm optimization (PSO) was employed to determine the model parameters. Finally, the applicability of AdaBoost-XXT was tested in Linyi watershed with large-scale and semi-arid conditions and in Youshuijie catchment with small-scale area and humid climate. The results show that modified AdaBoost.RT algorithm significantly improves the performance of XXT in daily runoff prediction, especially for the large-scale watershed or low runoff periods, in terms of Nash–Sutcliffe efficiency coefficients and coefficients of determination. Furthermore, the AdaBoost-XXT has the more satisfactory generalization ability in processing input data, especially in Linyi watershed. Thus the method of using this modified AdaBoost.RT to enhance model performance is promising and easily extended to other process-based rainfall–runoff models.     

Efficient FPGA implementation of DWT and modified SPIHT for lossless image compression

In this paper, we present an implementation of the image compression technique set partitioning in hierarchical trees (SPIHT) in programmable hardware. The lifting based Discrete Wavelet Transform (DWT) architecture has been selected for exploiting the correlation among the image pixels. In addition, we provide a study on what storage elements are required for the wavelet coefficients. A modified SPIHT (Set Partitioning in Hierarchical Trees) algorithm is presented for encoding the wavelet coefficients. The modifications include a simplification of coefficient scanning process, use of a 1-D addressing method instead of the original 2-D arrangement for wavelet coefficients and a fixed memory allocation for the data lists instead of the dynamic allocation required in the original SPIHT. The proposed algorithm has been illustrated on both the 2-D Lena image and a 3-D MRI data set and is found to achieve appreciable compression with a high peak-signal-to-noise ratio (PSNR).     

双向搜索蚁群算法在QoS单播路由中的应用

近几年来,网络的QoS路由问题已经成为一个研究热点。考虑到现有解决方法的一些不足,引入了一种改进的蚁群算法并应用于QoS单播路由问题。该算法针对网络路由问题,对原算法的信息素更新策略进行了修改,同时结合了网络化简策略和双向搜索策略。与现有QoS路由算法比较的仿真结果表明,该算法能够满足QoS单播路由的要求,并且具有较好的最优解求解能力、较快的收敛速度和较强的鲁棒性。     

AdaBoost 及其改进算法综述

AdaBoost算法是目前人脸检测领域最有效的方法之一,自该算法提出以来,很多研究者做了深入的研究分析和改进工作。基于AdaBoost算法受到众多研究者的重视,综述了AdaBoost及其改进算法。从AdaBoost算法出发,着重分析了AdaBoost算法的优缺点,并以此为基础对其改进算法作系统的分析和介绍,对改进算法进行了简单归类。最后,指出了算法未来的几个发展方向。     

Integrated process planning and scheduling: an enhanced ant colony optimization heuristic with parameter tuning

This study develops an enhanced ant colony optimization (E-ACO) meta-heuristic to accomplish the integrated process planning and scheduling (IPPS) problem in the job-shop environment. The IPPS problem is represented by AND/OR graphs to implement the search-based algorithm, which aims at obtaining effective and near-optimal solutions in terms of makespan, job flow time and computation time taken. In accordance with the characteristics of the IPPS problem, the mechanism of ACO algorithm has been enhanced with several modifications, including quantification of convergence level, introduction of node-based pheromone, earliest finishing time-based strategy of determining the heuristic desirability, and oriented elitist pheromone deposit strategy. Using test cases with comprehensive consideration of manufacturing flexibilities, experiments are conducted to evaluate the approach, and to study the effects of algorithm parameters, with a general guideline for ACO parameter tuning for IPPS problems provided. The results show that with the specific modifications made on ACO algorithm, it is able to generate encouraging performance which outperforms many other meta-heuristics.     

Toolpath planning algorithm for the ablation process using energy sources

Ablation processes using various energy sources such as lasers, electrical power and ultrasonic sources have been widely used in industry to ablate workpieces made of hard-to-cut and temperature resistive materials. Even though the cutting mechanism of the ablation process is different from that of the mechanical cutting process, an identical toolpath of the mechanical cutting process has been applied to the ablation process. An inappropriate toolpath for the ablation process may result in a lower dimensional accuracy of the ablated part. Therefore, a new toolpath planning algorithm considering the characteristics of the energy source is required. In this paper, a toolpath planning algorithm for the ablation process is proposed. The proposed algorithm consists of three steps: (1) The generation of a valid toolpath element, (2) the storage of toolpath elements and the creation of sub-groups, (3) the linking of sub-groups. New guidelines on the toolpath demanded by the ablation process are studied. A new idea involving the use of a storage matrix is applied to the storage of toolpath elements and the creation of sub-groups. In order to verify the applicability of the proposed algorithm, the proposed toolpath planning algorithm has been implemented and tested with practical examples.