关于《求解LP问题的部分基变量算法》的勘误及补正

文章针对周康等人的《求解LP问题的部分基变量算法》一文进行了分析,指出其文中算法原理及算法步骤存在的一些错误,补正了算法的不完善之处,并通过数值试验验证算法的计算性能。     

基于结构继承的贝叶斯网结构学习优化设计

采用遗传算法建立贝叶斯网络的优化学习结构,一直是贝叶斯网络研究倍受关注的课题.传统遗传算法的个体设计存在需要反复进行无环性检验的问题,降低了进化效率.针对这个问题,提出一种新的个体编码方式.考虑到进化过程中家族得分的可继承性,提出基于家族继承的结构评分改进算法,进而设计相应的改进遗传算法.实验结果表明,改进算法在BN建网精度与效率上都得到明显提升.     

基于遗传算法的关联议题并发谈判

基于遗传算法的并发谈判在电子商务应用中具有独特的优势,但已有的研究尚未考虑议题之间的相关性、动态权重的变化规则依赖于对手信息的获取,极大地限制了其使用价值.对此,提出议题分组的方法以解决议题的相关性问题,而议题权重的变化则采取从历史资源中发掘知识的方法进行动态调整.构建了基于遗传算法的关联性议题并发谈判模型,给出了模型的形式化描述、谈判算法设计和动态权重更新方案.通过对模型的实验和比较分析,证实了该方案能够更方便地满足用户谈判的多样性需求,解决谈判中议题关联性的问题,而且能够快速、有效地得出最优谈判结果.     

基于Matlab的0-1背包问题的动态规划方法求解

背包问题是经典的NP-hard组合优化问题之一,在经济管理、资源分配、投资决策、装载设计等领域有着重要的应用价值。文中用动态规划方法解决0-1背包问题,通过在Matlab6.5环境下对其算法进行测试和与其他方法对比分析,表明应用该方法可节省大量的计算时间,因而具有更高运行效率。     

Using immune genetic algorithm based hybrid techniques for short-term unit commitment problem

This paper presents a hybrid chaos search (CS), immune algorithm (IA)/genetic algorithm (GA), and fuzzy system (FS) method (CIGAFS) for solving short-term thermal generating unit commitment (UC) problems. The UC problem involves determining the start-up and shut-down schedules for generating units to meet the forecasted demand at the minimum cost. The commitment schedule must satisfy other constraints such as the generating limits per unit, reserve, and individual units. First, we combined the IA and GA, then we added the CS and the FS approach. This hybrid system was then used to solve the UC problems. Numerical simulations were carried out using three cases: 10, 20, and 30 thermal unit power systems over a 24 h period. The produced schedule was compared with several other methods, such as dynamic programming (DP), Lagrangian relaxation (LR), standard genetic algorithm (SGA), traditional simulated annealing (TSA), and traditional Tabu search (TTS). A comparison with an immune genetic algorithm (IGA) combined with the CS and FS was carried out. The results show that the CS and FS all make substantial contributions to the IGA. The result demonstrated the accuracy of the proposed CIGAFS approach.     

武钢二炼钢厂炉机匹配系统算法研究

武钢集团第二炼钢厂的炉机匹配系统可简化为两道工序的车间作业排程问题。其问题的关键在于合理调配3台转炉的工作时段以满足4台铸机的不间断运转。本文提出了一种快速有效的算法——压缩-扩张算法，为整个系统的最后实现，提供了最关键的支持。     

Fatigue life calculation by means of the cycle counting and spectral methods under multiaxial random loading

The paper contains a new algorithm for estimation of fatigue life in HCF regime under multiaxial random loading using spectral methods. Loading of Gaussian distribution and narrow‐ and broad‐band frequency spectra were assumed. Various characteristic states of multiaxial loading were considered. The equivalent stress history was determined with use of the failure criteria of multiaxial fatigue based on the critical plane. For determination of the critical plane position, the method of variance was applied. During simulation, the authors compared the results obtained by a spectral method in the frequency domain with those from the rain‐flow algorithm in the time domain. The paper also contains the results of fatigue tests for 18G2A structural steel subjected to bending and combined bending with torsion. The tests were performed in order to verify the proposed algorithms for determination of fatigue life. It has been shown that under multiaxial random loading results of fatigue life calculated according to the considered algorithms in frequency and time domains are well correlated with the results of experiments.     

基于离散泰勒级数的新型联想记忆系统

基于离散泰勒级数提出一种对任意阶多维函数可实现无差逼近的新型联想记忆系统，详细讨论了该系统的插值算法、训练规则及寻址机制，新型联想记忆系统相对于CMAC具有逼近精度更高、占用存储单元较少、学习速度较快等优点，该系统在信号处理、模式识别、过程建模及高精度实时智能控制等领域具有广泛的应用价值，仿真实例表明了系统的可行性与有效性。     

遗传-多点退火接力混合算法的应用

遗传-多点退火接力混合算法是先进行遗传算法操作,再接力使用模拟退火法操作的一种尝试。其关键在于遗传算法中变异的处理及退火中初始温度和降温值的处理。给出了该方法的基本过程和原型过程的数学描述,对算法中的罚因子,变异情况及温度值的选取进行了分析。通过具体实例的计算结果表明,将此方法用于非线性约束优化是可行的。