利用改进的HBDE算法求解MAX-k-SAT问题

目前,利用进化算法求解组合优化问题已成为智能计算领域中的研究热点。本文基于二进制差分演化算法和动态变邻域搜索相结合提出了一种求解最大可满足问题(MAX-k-SAT)的改进算法(记为IBDE),通过与遗传算法和Johnson算法对一系列随机大规模MAX-k-SAT实例的求解比较表明:IBDE是一种求解MAX-k-SAT问题非常有效的新方法。     

Modified Shifting Bottleneck Heuristic for Scheduling Problems of Large-Scale Job Shops

A modified shifting bottleneck algorithm was proposed to solve scheduling problems of a large-scale job shop.Firstly,a new structured algorithm was employed for sub-problems so as to reduce the computational burden and suit for large-scale instances more effectively.The modified cycle avoidance method,incorporating with the disjunctive graph model and topological sort algorithm,was applied to guaranteeing the feasibility of solutions with considering delayed precedence constraints.Finally,simulation experiments were carried out to verify the feasibility and effectiveness of the modified method.The results demonstrate that the proposed algorithm can solve the large-scale job shop scheduling problems(JSSPs) within a reasonable period of time and obtaining satisfactory solutions simultaneously.     

基于KMM匹配的参数迁移学习算法

当训练数据和测试数据来自不同的领域或任务以至于训练数据和测试数据的分布不相同时,需要进行知识的迁移.本文提出一种基于实例KMM匹配的参数迁移学习方法.利用KMM算法估计每个源领域实例的权重,再利用得到的权重,把这些实例应用到基于参数的迁移学习方法中.把该迁移学习算法应用到无线网络定位问题中时,该方法的定位准确度要高于单...     

混合遗传算法在随机规划问题中的应用

以含有机会约束的生产管理动态规划问题为例,基于随机模拟技术的混合遗传算法实现最优化决策,构造了数学模型。采用ＶＢ编辑,计算机模拟结果显示该模型能很好解决生产过程中的最优化决策问题,它是简单的基于二进制编码的遗传算法所不能解决的。该算法具有很高的鲁棒性,避免了在局部最优解附近徘徊,且因为随机规划问题要求许多数学知识,而算法本身并不要求对优化问题的性质作一些深入的数学分析,从而对那些不太熟悉数学理论和     

基于KL-DE算法的抛物型参数识别

为了降低将抛物型参数的维数,把参数假定为协方差已知的随机函数,并进行Karhunen-Loeve法分解,然后利用遗传算法求解此反演问题。通过仿真结果表明,改进算法可为偏微分方程的参数识别提供一个有效的工具。     

一种求解最大二等分问题的分散搜索算法

最大二等分问题是图论中的一个NP困难问题.本研究提出一种基于分散搜索框架的启发式算法求解最大二等分问题.该分散搜索算法采用Kernighan-Lin算法作为局部搜索算法,利用解的质量和解之间的距离构造参考集,通过两个可行解构造新的可行解.利用一些标准测试例子测试算法,实验结果与现存算法所得结果比较,表明该算法是有效的.     

具有可加白噪音的耦合系统的同步

在单边Lipschitz耗散条件下,考虑具有可加白噪音的耦合系统的两种同步现象,即不同解之间的同步和同一个解的不同分量之间的同步.首先证明了该耦合系统存在单点集随机吸引子,从而发生不同解之间的同步现象,此外该随机吸引子还是系统的唯一平稳解.然后证明了当耦合系数趋于无穷大时,该系统解的每一个分量在有限时间区间内一致地趋于平均系统的平稳解.     

求解组合优化问题的组合遗传算法

构造了求解组合优化问题的组合遗传算法。这个方法的主要优点是优化效果好 ,计算效率高以及通用性。模拟结果验证了该方法的有效性。它能应用到求解许多组合优化问题。     

Node ordinal encoded genetic algorithm for the optimal allocation of water resources

The shortage of water supply and the increasingdemand for water resources is a severe problem, andthe optimal allocation is the key to solving this prob lem in management of water resources. It is very dif ficult to solve the large scale discrete problem of waterresources programming because of the intricate rela tion between resources and environment. Combina tion exploding exists in traditional programmingmethods, such as enumerative and dynamic program ming methods. People are …     

多目标0 1规划的元胞竞争决策算法

将元胞演化规则与竞争决策算法相结合,提出了一种求解多目标0-1规划问题的元胞竞争决策算法.大量数据测试和验证表明,该算法能有效提高非劣解的分布性和多样性.     

一种基于禁忌搜索方法的作业车间调度

提出了一种解决作业车间调度最短完工时间问题的启发式算法．该算法中采用了变禁忌表长度策略的禁忌搜索方法．在禁忌搜索过程中利用完工时间（makespan）的一个下界作为判断一个解好坏的辅助量，由于得到该下界所需的计算量远远小于完工时间的，因此大大地减少了禁忌搜索过程的计算时间．从对一组问题基准实例的实验计算结果看，该算法在合理的计算时间内，得到了比当前没有使用转换瓶颈技术的最好的禁忌搜索算法之一的TSAB算法更好的结果．     

轨道路径约束的散货卸船机调度优化策略

基于对卸船机调度特征的描述,建立了以最小化卸载作业完成时间为目标的卸船机调度优化模型,设计了混合遗传算法组件以获得问题近似最优解,通过松弛原问题中的难约束,推导了松弛问题的下界并作为原问题的下界.同时,对具有不同规模的问题进行实例计算与分析.结果表明,所设计的混合遗传算法能够在可接受的计算时间内获得合理的解.     

Unusual phase transitions in ferroelectric nanodisks and nanorods

Bulk ferroelectrics undergo structural phase transformations at low temperatures, giving multi-stable (that is, multiple-minimum) degenerate states with spontaneous polarization. Accessing these states by applying, and varying the direction of, an external electric field is a key principle for the operation of devices such as non-volatile ferroelectric random access memories (NFERAMs). Compared with bulk ferroelectrics, low-dimensional finite ferroelectric structures promise to increase the storage density of NFERAMs 10,000-fold. But this anticipated benefit hinges on whether phase transitions and multi-stable states still exist in low-dimensional structures. Previous studies have suggested that phase transitions are impossible in one-dimensional systems, and become increasingly less likely as dimensionality further decreases. Here we perform ab initio studies of ferroelectric nanoscale disks and rods of technologically important Pb(Zr,Ti)O3 solid solutions, and demonstrate the existence of previously unknown phase transitions in zero-dimensional ferroelectric nanoparticles. The minimum diameter of the disks that display low-temperature structural bistability is determined to be 3.2 nm, enabling an ultimate NFERAM density of 60 x 10(12) bits per square inch-that is, five orders of magnitude larger than those currently available. Our results suggest an innovative use of ferroelectric nanostructures for data storage, and are of fundamental value for the theory of phase transition in systems of low dimensionality.     

Scheduling Step-Deteriorating Jobs on Parallel Machines by Mixed Integer Programming

Production scheduling has a major impact on the productivity of the manufacturing process. Recently, scheduling problems with deteriorating jobs have attracted increasing attentions from researchers. In many practical situations,it is found that some jobs fail to be processed prior to the pre-specified thresholds,and they often consume extra deteriorating time for successful accomplishment. Their processing times can be characterized by a step-wise function. Such kinds of jobs are called step-deteriorating jobs. In this paper,parallel machine scheduling problem with stepdeteriorating jobs( PMSD) is considered. Due to its intractability,four different mixed integer programming( MIP) models are formulated for solving the problem under consideration. The study aims to investigate the performance of these models and find promising optimization formulation to solve the largest possible problem instances. The proposed four models are solved by commercial software CPLEX. Moreover,the near-optimal solutions can be obtained by black-box local-search solver LocalS olver with the fourth one. The computational results show that the efficiencies of different MIP models depend on the distribution intervals of deteriorating thresholds, and the performance of LocalS olver is clearly better than that of CPLEX in terms of the quality of the solutions and the computational time.     

基于网络响应面的多目标优化方法

为提高多目标优化算法的收敛性以及Pareto解的分布均匀性,构建了基于网络响应面的多目标优化方法.将前馈（BP）网络以及自适应共振（ART）网络的优点相结合,充分利用各子目标每1次独立优化时获得的最优解,并将其作非占优判断后作为初始样本自适应地构建网络响应面,从而提高了Pareto解的收敛性以及多样性指标.对网络获得的每个新类进行各子目标值计算,同时对该子目标值做相似度计算,进一步剔除相似度高的样本,从而提高了Pareto解的分布性指标.通过常用的多目标优化测试函数验证该方法,并与改进的非支配排序遗传算法（NSGA-Ⅱ）以及随机权和算法作对比,结果表明该方法能明显改善多目标优化方法的各性能指标.     

Semiparametric Preference Learning

Unlike traditional supervised learning problems,preference learning learns from data available in the form of pairwise preference relations between instances.Existing preference learning methods are either parametric or nonparametric in nature.We propose in this paper a semiparametric preference learning model,abbreviated as SPPL,with the aim of combining the strengths of the parametric and nonparametric approaches.SPPL uses multiple Gaussian processes which are linearly coupled to determine the preference relations between instances.SPPL is more powerful than previous models while keeping the computational complexity low （linear in the number of distinct instances）.We devise an efficient algorithm for model learning.Empirical studies have been conducted on two real-world data sets showing that SPPL outperforms related preference learning methods.     

混合变分不等式和非扩张映射解的迭代算法

引入和研究了一类更一般的混合变分不等式,这类混合变分不等式问题包含了许多已知的变分不等式、相补问题等作为特例.利用广义Wiener-Hopf方程技巧给出了一个求解这类混合变分不等式问题解集合和非扩张映射不动点集合公共元素的迭代算法,并在算子是松弛强制和Lipschitzian连续的条件下证明了该算法的收敛性.所得结果可以看作是一种新的和对已有一些结论的推广和改进.     

一种基于ICA的盲源分离定点迭代算法

介绍了一种基于ICA的定点速代算法，并给出算法的模型、步骤和仿真结果。该算法以峰度作为独立性判决准则，在迭代过程中，使用定点算法，快速有效地分离出任意分布的非高斯独立源信号。实验表明，与传统的基于随机梯度的ICA算法相比，谊算法具有收敛速度快，无需动态参数的优点，是一种高效可靠的盲信号分离算法。     

有时间窗配送车辆调度问题的禁忌搜索算法

在对有时间窗配送车辆调度问题进行描述的基础上,建立了该问题的基于直观描述的数学模型.通过设计一种新的解的表示方法构造了求解该问题的禁忌搜索算法,并以21个节点的运输网络为例进行了实验计算.计算结果表明,用作者设计的禁忌搜索算法求解有时间窗配送车辆调度问题,不仅可以取得很好的计算结果,而且算法的计算效率较高,收敛速度较快,计算结果也较稳定.     

基于贪婪启发式的多期多目标动态网络选址

为弥补现有选址模型考虑需求变化及客户满意度的不足,研究了随机需求环境下的配送中心选址并设计了衡量客户满意度的函数. 运用随机机会约束规划为基本建模工具,将模型设计拓展到多期规划决策领域并构建了动态多期多目标选址模型,模型不仅考虑了最小化配送中心运作成本,而且考虑了客户最大满意度;运用主要目标法将多目标选址模型转化为单目标选址模型,采用满意度高优先的客户指派原则设计了贪婪启发式求解算法. 算例结果表明,模型的非劣解包含了传统的以最小化物流成本为目标的选址模型的最优解,从而为配送中心选址提供更加灵活全面的决策依据.