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Then a filled function method for the integer programming problem is proposed,which tries to find a better discrete local minimal solution of the problem by minimizing a filled function.

该方法通过寻找填充函数的离散局部极小解以期找到整数规划问题的比当前离散局部极小解好的解。该文的算法是直接法,数值试验表明算法是有效的。

Which are important in object-relational databases, and how to translate the select-from-where cause into representations of monoid system are discussed.

发展了复杂水火电系统开停机优化的综合优化算法,在解决复杂的混合整数规划和非线性问题上向前推进了一步。

By constructing a job-schedule network that can present job-time relationship,the FJSP is transformed to a network flow problem,and a 0-1 integer programming mathematical model is developed.

针对一般形式的固定工件排序问题(即可用机器数是有限的,存在机器与工件间匹配约束,以机器分配成本最小为优化目标),作者通过建立描述工件间时序关系的工件时序网络,将固定工件的排序问题转化为沿工件时序网络的网络流问题,并建立了0-1整数规划数学模型。

Secondly, the power system fault diagnosis analytic model which use both protect andswitch action information is proposed in this paper, it can be described as 0-1 integerprogramming with nonrestraint, reshut break is introused in the analytic model and introducethe contribution factor to the protect, this model solve the fault diagnosis problem in which theprotect information is lack in a certain extent, and present the experienced formular which isused to decide all kinds of protect contribution factor.

然后,提出同时利用保护和断路器动作信息的电力系统故障诊断的解析模型,其可以描述为一个无约束 0-1 整数规划问题,将重合闸引入故障诊断的解析模型并且对保护引入贡献因子,给出确定各种保护贡献因子的经验公式。这种模型在一定程度上解决了数据信息不完整时的电力系统故障诊断问题。

It is pos ible to solve some particular types of integral linear programming problems by virtue of LCS-orientated algorithm or microprocessor.

本文用字编码函数的方法,得到求解LCS的数值模型,证明可用求解Tomograph问题的算法和硬件求解LCS问题,以及可以用LCS的算法和硬件求解某种类型的整数规划问题。

Characterizing plant phototropism, the algorithm looks the feasible region of integer programming as plant growth environment, and determines the growth probability on different growth points according to the changes of the object function.

该算法从植物的向光性特点出发,将整数规划的可行域作为植物的生长环境,根据各可行解目标函数的变化情况确定植物的生长信息,进而模拟出向光源迅速生长的植物生长动力学模型。

Considering portfolio selection issue with the realistic environments of the stock market in China,we propose Probability Criterion Model in this paper.

考虑到我国证券交易过程中许多限制性的规定及现实投资者并非完全理性的决策行为,给出了概率准则组合投资的收益-损失风险双目标整数规划模型。

On global optimal algorithms, a heuristic 0-1 Integer Liner Programming algorithm is achieved, which combines heuristic enumeration method and revised simplex method. Simulation experiments show that the degree and optimization efficiency in our algorithm is obviously improved compared with the MATLAB 7 bintprog function that is a 0-1 integer programming algorithm. Moreover our algorithm isn\'t relevant to the scale changes of Web services composition and candidate service sets, thus it is applicable for the scenes that the scales of Web services composition changed dynamically. But for Web services composition with service alliance, the algorithm is unable because the non-linear global optimal model of the fitness function and QoS constraints can\'t be expressed in linear mode.

在全局优化算法研究上,基于启发式0-1整线性规划算法结合了修正单纯形法和启发式枚举法,仿真实验表明该算法与MATLAB 7的0-1整数规划方法比较,在优化程度及优化效率上得到了显著改进,并且对服务组合和候选服务集合的规模变化没有明显的相关性,因而该算法可用于服务组合规模动态变化的场景,但该算法不能应用于存在服务联盟的非线性全局优化模型。

Secondly, we consider simutaneously in our model multiple market frictions such as tax, transaction costs and other typical market restrictions.

由此建立了一个基于CVaR并兼顾市场摩擦的新型投资组合选择模型,该模型为一大规模混合整数规划问题,可用已有算法软件有效求解。

The constructing process of the algorithms itself indicate that they are brevity and have definite geometric meaning, scientific iterative terminal criterions and no strict requirement to function. Finally, some digital experimentation is presented to indicate the algorithms application in solving the problem of maximum of function, transcendental equation,integer programming and so on. The results indicate that the algorithms have more global and more adaptability compared to traditional algorithms and have more calculating efficiency and more scientific iterative terminal criterions compared to some present popular artificial intelligence algorithms.

算法的构造过程本身表明了该算法简单明了、几何意义明确、迭代终止准则科学、对函数的要求较低;最后举了几个数值试验的例子以说明该类算法在求函数的最值,解超越方程以及整数规划等问题中的应用;数值试验的结果标明该算法比单纯由"微分"思想演化而来的传统算法有更好的全局性和对问题的更广泛的适应性,比现在流行的一些人工智能方法有更高的运算效率和更适当的迭代中止准则。

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