求Ramsey数最优下界值的递归算法

要确定每个具体的Ramsey数的数值是相当困难的,至今人们只求出了为数很少的几个Ramsey数的数值.人们在研究Ramsey数性质的同时,也在估计Ramsey数的数值,得出了某些Ramsey数的下界值,但工作进展缓慢.本文提出了一种计算Ramsey数最优下界值的递归算法,该算法利用当今关于Ramsey数的最新结果,能得出Ramsey数的目前最优下界值.1 算法描述不妨将本算法定名为G,参数个数为1个以上(可变化),算法允许递归调用,其输出值为Ramsey数的目前最优下界值.C(k_1,k_2…,k_n)表示以k_1,k_2…,k_n作为输入,通过算法G所得到的输出结果,即C(k_1,k_2…,k_n)表示的是G算出的Ramsey数N(k_1,k_2,…,k_n;2)的目前最优下界值,其中N(k_1,k_2…,k_n;2)的含意与文献[2]中有关含意相同.算法G:     

A New Integrated Design Method Based on Fuzzy Matter-Element Optimization

This paper puts forward a new integrated design met ho d based on fuzzy matter-element optimization.On the based of analyzing the mod el of multi-objective fuzzy matter-element , the paper defines the m atter-element weightily and changes solving multi-objective fuzzy optimization into solving dependent function K(x) of the single-objective optimization according to the optimization criterion. The paper particularly describes the realization approach of GA process of multi -objective fuzzy matter-eleme...     

Introduction to Ant Colony Algorithm and Its Application in CIMS

Ant colony algorithm is a novel simulated ecosystem e volutionary algorithm, which is proposed firstly by Italian scholars M.Dorigo, A . Colormi and V. Maniezzo. Enlightened by the process of ants searching for food , scholars bring forward this new evolutionary algorithm. This algorithm has sev eral characteristics such as positive feedback, distributed computing and stro nger robustness. Positive feedback and distributed computing make it easier to find better solutions. Based on these characteristics...     

互补问题中Gauss-Newton方法全局收敛性的推广(英文)

研究了由Subramamian为求解互补问题提出的阻尼Gauss-Newton方法的收敛性质，在较弱的条件下，给出了一个全局收敛效果，这个结果是Subramanian PK (1993)和（1997）中相应结果的一个推广。     

利用二次贝齐尔函数的一维优化算法

本文利用贝齐尔函数良好的保型性质,将它作为拟合函数,构造了一个一维优化算法。数值实验表明,对于高度非线性的目标函数,新算法具有很强的适应性,比同类算法更有效。     

上海郊区居民和台湾高山族的体质比较

收集了上海郊区13个具有明显方言差异人群的头面部数据4项，和台湾高山族10个群体的参数进行聚类分析，发现上海郊区居民中的南方土著人群与台湾高山的遗传关系较近。     

A floating-point genetic algorithm for solving the unit commitment problem

This paper proposes a floating-point genetic algorithm (FPGA) to solve the unit commitment problem (UCP). Based on the characteristics of typical load demand, a floating-point chromosome representation and an encoding–decoding scheme are designed to reduce the complexities in handling the minimum up/down time limits. Strategic parameters of the FPGA are characterized in detail, i.e., the evaluation function and its constraints, population size, operation styles of selection, crossover operation and probability, mutation operation and probability. A dynamic combination scheme of genetic operators is formulated to explore and exploit the FPGA in the non-convex solution space and multimodal objective function. Experiment results show that the FPGA is a more effective technique among the various styles of genetic algorithms, which can be applied to the practical scheduling tasks in utility power systems.     

关于可达矩阵的求法探讨

在《离散数学》、《图论》课程中 ,用矩阵表示图时 ,涉及到一类重要的矩阵——可达矩阵 ,它是判别图中任意两点是否有通路的重要手段 ,也是求强分图的重要方法 ,但是可达矩阵的求法比较复杂 .本文针对这一问题 ,对可达矩阵的求法进行了改进 ,提出了一种简单可行的算法 .     

A comparison of two algorithms for the assignment problem

State-of-the-art computational results have shown that the shortest augmenting path (SAP) methods are more efficient than other primal-dual and primal-simplex based methods for solving the linear assignment problem on uniprocessor computers. There is, however, some controversy concerning their merits when compared with Bertsekas' auction algorithm on multiprocessor computers. In this study we investigate the performance of these competing methods on the Alliant FX/8. For each method, theoretical motivation, sources of parallelism and computational results are presented.     

不等式约束优化问题的一个势函数

基于Carroll(1961)建立的罚函数，本文给出了不等式约束优化问题的一个势函数，并且讨论了该函数的性质．最后证明了在此基础上建立的对偶算法具有Q-线性收敛性．