一般多值向量变分不等式问题

本文引入一般多值向量变分不等式问题（GMVVI）,这推广和统一了现有的向量变分不等式,文内还引入了弱C－伪单调映射和半连续映的概念,在弱C－伪单调性和半连续性的假设下,给出了（GMVVI）的广义线性化引理和解的存在定理,本文的结果即使对一般向量变分不等式问题和广义向量变分不等式问题也是全新的。     

具强制条件的向量均衡问题

研究锥伪单调、锥拟凸和上锥连续映射在某种强制性条件下的向量均衡问题解集的特征,建立强制性条件与向量均衡问题解集的关系,得到对偶向量均衡问题局部解集含于向量均衡问题解集的性质和向量均衡问题解集的非空性条件,给出在锥伪单调、锥拟凸和上锥连续映射条件下向量均衡问题解集的非空有界性与强制性条件的等价性．     

向量均衡问题

本首先引进了集值映射的伪单调性，利用Ky Fan引理以及KKM映射对一般向量均衡问题建立了相应的存在性定理．     

伪单调型向量F-互补问题可行集的最小元问题

本文引入了几类向量F-互补问题并给出了向量F-互补问题与广义向量变分不等式之间的关系.通过定义向量F-互补问题的可行集,研究了伪单调型向量F-互补问题的可行集的最小问题,推广了已有的一些结果.     

W—空间的平衡问题

得到了Ｗ－空间数量情形的平衡问题的解的若干存在性定理,其结果在没有单调性条件下将文［１、２］的相应定理由Ｈａｕｓｄｏｒｆ拓扑向量空间推广到了Ｗ空间;然后通过引入ξ函数将其转化为向量形式,从而得到向量平衡问题的解的若干存在性定理,其结果在没有单调性条件下将文［１、３］的相应定理由Ｈａｕｓｄｏｒｆ拓扑向量空间推广到了Ｗ空间,且减弱了文［４、５］相应定理的连续性条件．     

函数强伪凸性与映射强伪单调性

1　引　　言Schaible在[1]中引入七类单调映射,并证明对其中六类,函数的某种广义凸性都和相应的梯度单调性等价,只有函数强伪凸和梯度强伪单调的等价性是否成立作为公开问题.其后,Schaible又在[2]中通过一个例子否定了两者的等价性,并引入了较弱的函数强伪凸和映射强伪单调的概念,在函数二次可微的条件下证明了函数强伪凸和梯度强伪单调等价.我们将引入强于[2]中概念的强伪凸和强伪单调性,对给出的定义,不附加条件便可保证函数强伪凸性和梯度强伪单调性等价.同时,对[2]中的一个错误予以指出,并给出正确的反例.还就[1]中问题给出远比[2]中简…     

含参集值弱向量平衡问题解集映射的半连续性

在线性度量空间中,运用标量化技巧在没有单调性与C-凹性假设下得到了含参集值弱向量平衡问题解集映射上/下半连续性的充分性条件.所得结果改进了已有文献的相应结果,并通过例子验证了所得结果.     

向量均衡问题的超有效性的对偶形式

在局部凸空间中引进了向量均衡问题的强超有效解、C-强超有效解、弱超有效解, C-弱超有效解、齐次超有效解、 C-齐次超有效解的概念,并在局部凸空间中用极理论为工具讨论了向量均衡问题的 C-弱超有效解, C-超有效解, C-齐次超有效解,以及C-强超有效解的对偶形式. 又在赋范线性空间中讨论了向量均衡问题的以上各种超有效解之间的等价性,并且在赋范线性空间具正规锥的条件下讨论了向量均衡问题的以上各种超有效解的对偶形式. 作为它的应用,给出了向量优化问题各种超有效解的对偶形式.     

具有控制结构的向量均衡问题与解集的性质

提出一种具有控制结构的向量均衡问题与向量映射的新的伪单调性概念,得到具有控制结构的向量均衡问题解的存在性及其解集的紧凸性．作为应用,得到具有控制结构的向量变分不等式与互补问题的解．     

含参广义向量均衡问题有效解的稳定性

在不需要映射的单调性和解映射信息的条件下,本文讨论了一类含参广义向量均衡问题有效解映射的下半连续性和Hausdorff上半连续性.利用映射的严格C-凹性和C-似凸性,本文得到了该类含参广义向量均衡问题有效解映射的下半连续性.进一步,利用标量化方法,证明了该类含参广义向量均衡问题有效解映射的Hausdorff上半连续性.     

Minimum values over the efficient set in multiple objective decision making

In multiple objective decision making (MODM), it is often helpful to provide the decision maker (DM) with bounds on the values of each of the objectives. Ideal solutions are relatively easy to calculate and provide upper bounds on the value of each objective over the set of efficient solutions. Ideal solutions also provide lower bounds on the value of each objective over the ideal set. However, the lower bounds over the set of efficient solutions can be strictly less than the ideal lower bounds, but are, in general, more difficult to determine. Thus MODM procedures which utilize the ideal lower bound may overlook elements of the set of efficient solutions. This study explores the differences between the subset of the set of efficient solutions to a MODM problem bounded by its ideal solutions and the complete efficient set.     

Structural Properties of Tensors and Complementarity Problems

In this paper, one of our main purposes is to prove the boundedness of the solution set of tensor complementarity problems such that the specific bounds depend only on the structural properties of such a tensor. To achieve this purpose, firstly, we prove that this class of structured tensors is strictly semi-positive. Subsequently, the strictly lower and upper bounds of operator norms are given for two positively homogeneous operators. Finally, with the help of the above upper bounds, we show that the solution set of tensor complementarity problems has the strictly lower bound. Furthermore, the upper bounds of spectral radius are obtained, which depends only on the principal diagonal entries of tensors.     

An Algorithm for Strictly Convex Quadratic Programming with Box Constraints

1IntroductionWeconsiderastrictlyconvex(i.e.,positivedefinite)quadraticprogrammingproblemsubjecttoboxconstraints:t-iereA=[aij]isannxnsymmetricpositivedefinitematrix,andb,canddaren-vectors.Letg(x)bethegradient,Ax b,off(x)atx.Withoutlossofgeneralityweassumebothcianddiarefinitenumbers,ci相似文献   

集值映射最优化问题的严有效解集的连通性及应用

本文对集值映射最优化问题引入严有效解的概念．证明了当目标函数为锥类凸的集值映射时,其目标空间里的严有效点集是连通的;若目标函数为锥凸的集值映射时,其严有效解集也是连通的．作为应用,讨论了超有效解集的连通性．     

STRICTLY WEAK MAJOR EFFICIENT POINT OF SET AND ITS PROPERTIES

Abstract. In this paper, the strictly weak major efficient point of set is introduced. A functional as a separate function is constructed, therefore, a necessary and sufficient condition for the strictly weak major efficient point of set is established.     

Connectedness of the efficient set in strictly quasiconcave vector maximization

In this paper, the concepts of quasiconcave set and strictly quasiconcave set are introduced. By using these concepts, we get a new sufficient condition for the efficient outcome set to be connected. This leads to the connectedness of the efficient solution set in strictly quasiconcave vector maximization under the mild condition that the efficient frontier is closed.The authors would like to thank Professor E. U. Choo and the referees for their many valuable comments and helpful suggestions.     

Ranking scalar products to improve bounds for the quadratic assignment problem

The eigenvalue bound for the quadratic assignment problem (QAP) is successively improved by considering a set of k-best scalar products, related to the QAP. An efficient procedure is proposedto find such a set of k-best scalar products. A class of QAPs is described for which this procedure in general improves existing lower bounds and at the same time generates good suboptimal solutions. The method leaves the user with a large flexibility in controlling the quality of the bound. However, since the method is sensitive to input data it should only be used in combination with other bounding rules.     

A fast approximation algorithm for solving the complete set packing problem

We study the complete set packing problem (CSPP) where the family of feasible subsets may include all possible combinations of objects. This setting arises in applications such as combinatorial auctions (for selecting optimal bids) and cooperative game theory (for finding optimal coalition structures). Although the set packing problem has been well-studied in the literature, where exact and approximation algorithms can solve very large instances with up to hundreds of objects and thousands of feasible subsets, these methods are not extendable to the CSPP since the number of feasible subsets is exponentially large. Formulating the CSPP as an MILP and solving it directly, using CPLEX for example, is impossible for problems with more than 20 objects. We propose a new mathematical formulation for the CSPP that directly leads to an efficient algorithm for finding feasible set packings (upper bounds). We also propose a new formulation for finding tighter lower bounds compared to LP relaxation and develop an efficient method for solving the corresponding large-scale MILP. We test the algorithm with the winner determination problem in spectrum auctions, the coalition structure generation problem in coalitional skill games, and a number of other simulated problems that appear in the literature.     

Interval data without sign restrictions in DEA

Conventional DEA models assume deterministic, precise and non-negative data for input and output observations. However, real applications may be characterized by observations that are given in form of intervals and include negative numbers. For instance, the consumption of electricity in decentralized energy resources may be either negative or positive, depending on the heat consumption. Likewise, the heat losses in distribution networks may be within a certain range, depending on e.g. external temperature and real-time outtake. Complementing earlier work separately addressing the two problems; interval data and negative data; we propose a comprehensive evaluation process for measuring the relative efficiencies of a set of DMUs in DEA. In our general formulation, the intervals may contain upper or lower bounds with different signs. The proposed method determines upper and lower bounds for the technical efficiency through the limits of the intervals after decomposition. Based on the interval scores, DMUs are then classified into three classes, namely, the strictly efficient, weakly efficient and inefficient. An intuitive ranking approach is presented for the respective classes. The approach is demonstrated through an application to the evaluation of bank branches.     

THE SHIFTED-INVERSE POWER WEAK GALERKIN METHOD FOR EIGENVALUE PROBLEMS

This paper proposes and analyzes a new weak Galerkin method for the eigenvalue problem by using the shifted-inverse power technique. A high order lower bound can be obtained at a relatively low cost via the proposed method. The error estimates for both eigenvalue and eigenfunction are provided and asymptotic lower bounds are shown as well under some conditions. Numerical examples are presented to validate the theoretical analysis.