Two-phase TOPSIS of uncertain multi-attribute group decision-making

To solve the uncertain multi-attribute group decisionmaking of unknown attribute weights, three optimal models are built to decide the corresponding ideal solution weights, standard deviation weights and mean deviation weights. The comprehensive attribute weights are gotten through the product of the above three kinds of weights. And each decision maker's weighted decision matrices are also received by using the integrated attribute weights. The closeness degrees are also gotten by use of technique for order preference by similarity to ideal solution (TOPSIS) through dealing with the weighted decision matrices. At the same time the group decision matrix and weighted group decision matrix are gotten by using each decision-maker’s closeness degree to every project. Then the vertical TOPSIS method is used to calculate the closeness degree of each project. So these projects can be ranked according to their values of the closeness degree. The process of the method is also given step by step. Finally, a numerical example demonstrates the feasibility and effectiveness of the approach.     

Coordinating pricing and inventory decisions in a bounded production system with uncertain yield

Most inventory researches assume that production level can fluctuate arbitrarily. However, large fluctuation of the production level in many firms may be much costly. This paper addresses the coordinating pricing and inventory control problem in a bounded production system with uncertain yield, in which the production level is constrained between a maximum and minimum level in each period and the price can be adjusted dynamically. We show that the optimal policy is the interval base-stock-list-price policy. Also, we study the impact of the production bounds and uncertainty of the yield on the production system. Numerical experiments are also performed to study the impact of parameters on the system.     

一类高维随机矩阵置乱变换的周期

为了适合多媒体信息量庞大、存在数据冗余的特点,实施可证明安全、高效率的加密解密,使用了数论、近世代数、矩阵变换、算法分析等工具,对高维随机矩阵置乱变换的精确周期进行了研究。将实数域上线性代数的若干结果,推广到模素数有限域上,得到一类整数矩阵及其相关同余方程组之解的若干新性质;在此基础上将用于置乱的矩阵由2维扩展到任意高维,给出广泛一类高维随机整数矩阵A决定的置乱变换,在任意素数幂N=pr模数下,其周期T(A,N)的精确表达式,给出求精确周期算法的时间复杂度。结论可用于建立新型数字多媒体密码体制和信息隐藏体制,扩大其密钥空间,增加其安全性。     

一种区间数多属性决策方法在经济评价中的应用

研究了区间数多属性决策问题．利用区间数运算法则获得加权规范化矩阵．基于投影对TOPSIS法进行改进,通过各方案与理想解的相对贴近度进行方案排序或择优．并将方法应用于经济评价中,提高了决策的准确性和效率．结果表明：算例验证了该方法的可行性和有效性且具有操作简便和易于上机实现的特点．     

复杂制造协同物流网络资源规划的不确定性控制优化

复杂制造协同物流网络作为动态开放系统,其资源规划决策易受网络中随机不确定性因素影响而出现刚性敏感和稳定失效现象,此问题属于参数状态和概率分布均未知的完全不确定型问题.针对这种问题, 提出了带鲁棒控制约束的期望值模型, 并借助蒙特卡罗方法对资源规划决策中相关参数进行了不确定性仿真. 算例结果表明,与不添加鲁棒约束的优化模型相比, 该模型方法能有效控制不确定性因素的负影响, 增加资源规划决策的稳定性和连续性,为解决完全不确定型问题提供了新视角.     

多源不确定信息融合中的冲突证据快速合成方法

D-S证据组合规则在处理高冲突信息时,会得出与直觉相反的结论以及证据组合时计算量呈指数增长等问题。针对组合规则的不足,许多改进方法已提出,但各个方法都仍存在其局限性,如Murphy方法在很大程度上解决了冲突证据问题,并未解决计算量指数爆炸问题。基于对Murphy方法深入研究,归纳出相同证据的组合规律,给出了Murphy方法快速表达式,从而提出了一种快速的Murphy组合规则(fast Murphy combination rule, FMCR)。实验表明,新的组合规则在处理高冲突和多源不确定信息融合问题方面都是有效的,在保持Murphy组合规则计算正确性同时,显著地提高了计算速度。     

An assignment method for group decision making with uncertain preference ordinals

This paper presents an assignment method to solve the group decision making problem with uncertain preference information. The uncertain preference information is given as uncertain preference ordinals by decision makers. We first address the concept and calculation formulae of preference ordinal frequency, and then, uncertain preference ordinals are transformed into preference ordinal frequencies accordingly. Furthermore, a linear assignment model is built based on the derived preference ordinal frequencies, and the ranking of alternatives can be obtained by solving the model. Finally, a numerical example is used to illustrate the use of the proposed method.     

双函复合迭代下分形数集成形试验

 此前分形数集已经出现了动物形模样和三维自相似形态,那还只是单个函数的运算结果.这里进行的是两个函数复合迭代运算共同确定一个数集的试验.这种双函数集的形体模样既不是两单函数集的集合交并,也不是它们形体的几何合成,更像是与生物现象类似的数集杂交.双函数集的形态会传承其两单函数集的某些特征,又不同其单函数集而有自己的独特性.发现不仅两函数是而且两函数的复合迭代顺序也是双函数集形态的决定因素,表明分形数集存在同函异序双生子.高级双函数集的函数还有配型条件,对称双函数集的产生须要两函数的单函数集是同类对称数集,自相似双函数集的产生须要两函数的单函数集是同类自相似数集.文中提供了5个具有代表性的迭代函数,附图31幅展示了11个数集及自相似子集的三维形象.通过比对发现双函数集成形与动物杂交现象在多方面都有惊人的一致.推测动物基因结合有类似的顺序原理,生物基因信息不仅记录在基因中而且会记录在基因顺序中.     

基于离群因子的不确定数据生成算法

基于不确定数据的表示模型, 针对属性级不确定数据, 提出一种不确定数据生成算法AC UDGen（attribute level continuous uncertain data set generation algorithm）. 该算法通过引入离群点检测 LOF（local outlier factor）算法, 用每个数据对象的离群因子作为参数来控制不确定数据对象的扰动范围, 可很好地满足原始数据的分布特征, 解决了目前工作中缺乏原始数据分布特征的问题. 实验结果表明, 该算法生成的不确定数据集具有更好的聚类效果, 并降低了离群点对聚类结果的影响, 使每个数据对象MBR(minimum bounding rectangle)的大小可根据自身的分布特征自适应地变化.     

带有二项式系数的广义数Fibonacci的相关性质

该文通过研究广义的Fibonacci数,得到了许多重要的性质,并且,用二项式系数对广义Fibonacci数的一些性质进行了概括.