LARGE DEVIATIONS FOR INFINITE DIMENSIONAL AND REVERSIBLE REACTION－DIFFUSION PROCESSES

ＬＡＲＧＥＤＥＶＩＡＴＩＯＮＳＦＯＲＩＮＦＩＮＩＴＥＤＩＭＥＮＳＩＯＮＡＬＡＮＤＲＥＶＥＲＳＩＢＬＥＲＥＡＣＴＩＯＮ－ＤＩＦＦＵＳＩＯＮＰＲＯＣＥＳＳＥＳＣＨＥＮＪＩＮＷＥＮ（陈金文）（ＤｅｐｅｒｔｍｅｎｔｏｆＡｐｐｌｉｅｄＭａｔｈｅｍａｔｉｃｓ，Ｔ...     

MAJOR－EFFICIENT SOLUTIONS AND WEAKLY MAJOR－EFFICIENT SOLUTIONS OF MULTIOBJECTIVE PROGRAMMING

ＭＡＪＯＲ－ＥＦＦＩＣＩＥＮＴＳＯＬＵＴＩＯＮＳＡＮＤＷＥＡＫＬＹＭＡＪＯＲ－ＥＦＦＩＣＩＥＮＴＳＯＬＵＴＩＯＮＳＯＦＭＵＬＴＩＯＢＪＥＣＴＩＶＥＰＲＯＧＲＡＭＭＩＮＧ￥ＨＵＹＵＤＡ（Ｄｅｐｔ．ｏｆＡｐｐｌ．Ｍａｔｈ．，ＳｈａｎｇｈａｉＪｉａｏＴｏｎ...     

GENUS FIELDS， CONDUCTORS AND RELATIVE INTEGRAL BASES FOR ABELIAN FUNCTION FIELDS

ＧＥＮＵＳＦＩＥＬＤＳ，ＣＯＮＤＵＣＴＯＲＳＡＮＤＲＥＬＡＴＩＶＥＩＮＴＥＧＲＡＬＢＡＳＥＳＦＯＲＡＢＥＬＩＡＮＦＵＮＣＴＩＯＮＦＩＥＬＤＳ赵健强￥ＺｈａｏＪｉａｎｑｉａｎｇ（Ｄｅｐｔ．ｏｆＭａｔｈ．，Ｕｎｉｖ．ｏｆＳｃｉ．＆Ｔｅｃｈ．ｏｆＣｈｉｎａ...     

STABILITY OF MAJORLY EFFICIENT POINTS AND SOLUTIONS IN MULTIOBJECTIVE PROGRAMMING

ＳＴＡＢＩＬＩＴＹＯＦＭＡＪＯＲＬＹＥＦＦＩＣＩＥＮＴＰＯＩＮＴＳＡＮＤＳＯＬＵＴＩＯＮＳＩＮＭＵＬＴＩＯＢＪＥＣＴＩＶＥＰＲＯＧＲＡＭＭＩＮＧＧＵＧＵＯＨＵＡＡＮＤＨＵＹＵＤＡ（ＤｅｐａｒｔｍｅｎｔｏｆＭａｔｈｅｍａｔｉｃｓａｎｄＭｅｃｈａｎｉｃｓ...     

DISTRIBUTION OF THE (0,∞) ACCUMULATIVE LINES OF MEROMORPHHIC FUNCTIONS

ＤＩＳＴＲＩＢＵＴＩＯＮＯＦＴＨＥ（０，∞）ＡＣＣＵＭＵＬＡＴＩＶＥＬＩＮＥＳＯＦＭＥＲＯＭＯＲＰＨＨＩＣＦＵＮＣＴＩＯＮＳ￥ＷＵＳＨＥＮＧＪＩＡＮ（ＤｅｐａｒｔｍｅｎｔｏｆＭａｔｈｅｍａｔｉｃｓ，ＢｅｉｊｉｎｇＵｎｉｖｅｒｓｉｔｙ，ＢｅｉＪｉｎｇ１...     

CERTAIN SUBCLASSES OF ANALYTIC p－VALENT FUNCTIONS FOR OPERATORS ON HILBERT SPACE

ＣＥＲＴＡＩＮＳＵＢＣＬＡＳＳＥＳＯＦＡＮＡＬＹＴＩＣｐ－ＶＡＬＥＮＴＦＵＮＣＴＩＯＮＳＦＯＲＯＰＥＲＡＴＯＲＳＯＮＨＩＬＢＥＲＴＳＰＡＣＥＪｉａｎＭｉｎｇ（蹇明）（Ｄｅｐｔ．ｏｆＭａｔｈ．ＷｕｈａｎＵｎｉｖｅｒｓｉｔｙｏｆＴｅｃｈｎｏｌｏｇｙ，Ｗｕ...     

BOUNDARY VALUE PROBLEMS OF SINGULARLY PERTURBED INTEGRO－DIFFERENTIAL EQUATIONS

ＢＯＵＮＤＡＲＹＶＡＬＵＥＰＲＯＢＬＥＭＳＯＦＳＩＮＧＵＬＡＲＬＹＰＥＲＴＵＲＢＥＤＩＮＴＥＧＲＯ－ＤＩＦＦＥＲＥＮＴＩＡＬＥＱＵＡＴＩＯＮＳＺＨＯＵＱＩＮＤＥＭＩＡＯＳＨＵＭＥＩ（ＤｅｐａｒｔｍｅｎｔｏｆＭａｔｈｅｍａｔｉｃｓ,ＪｉｌｉｎＵｎｉｖｅ...     

HOPF BIFURCATION AND OTHER DYNAMICAL BEHAVIORS FOR A FOURTH ORDER DIFFERENTIAL EQUATION IN MODELS OF INFECTIOUS DISEASE

ＨＯＰＦＢＩＦＵＲＣＡＴＩＯＮＡＮＤＯＴＨＥＲＤＹＮＡＭＩＣＡＬＢＥＨＡＶＩＯＲＳＦＯＲＡＦＯＵＲＴＨＯＲＤＥＲＤＩＦＦＥＲＥＮＴＩＡＬＥＱＵＡＴＩＯＮＩＮＭＯＤＥＬＳＯＦＩＮＦＥＣＴＩＯＵＳＤＩＳＥＡＳＥＪＩＮＧＺＨＵＪＵＮ（井竹君）（Ｉｎｓｔｉｔ...     

FOURIER－CHEBYSHEV SPECTRAL METHOD FOR SOLVING THREE－DIMENSIONAL VORTICITY EQUATION

ＦＯＵＲＩＥＲ－ＣＨＥＢＹＳＨＥＶＳＰＥＣＴＲＡＬＭＥＴＨＯＤＦＯＲＳＯＬＶＩＮＧＴＨＲＥＥ－ＤＩＭＥＮＳＩＯＮＡＬＶＯＲＴＩＣＩＴＹＥＱＵＡＴＩＯＮＧＵＯＢＥＮＹＵ（郭本瑜）；ＬＩＪＩＡＮ（李健）；ＭＡＨＥＰＩＮＧ（马和平）（Ｄｅｐａｒｔｍｅｎｔｏ...     

GLOBAL STRUCTURE OF THE ORBITS OF A KIND OF N－DIMENSIONAL COMPETITIVE SYSTEMS

ＧＬＯＢＡＬＳＴＲＵＣＴＵＲＥＯＦＴＨＥＯＲＢＩＴＳＯＦＡＫＩＮＤＯＦＮ－ＤＩＭＥＮＳＩＯＮＡＬＣＯＭＰＥＴＩＴＩＶＥＳＹＳＴＥＭＳ￥ＣｈｅｎｇＣｈｕｎ－ｃｈｏｒ，Ｌｉｔｗｉｎ（郑振初）（ＨｏｎｇＫｏｎｇＩｎｓｔｉｔｕｔｅｏｆＥｄｕｃａｔｉｏｎ，香港...     

求群体多目标决策问题的一种可行方向交互算法

对于群体多目标决策问题,决策者可以各自的关于目标之间的权衡比表达其偏爱信息并进行决策.当个体权衡比具有加性性质时可得群体权衡比.本文以此构造一种求解群体非线性规划问题的交互算法.迭代中基于求解决非线性规划的Topkis-Veinott方法构造可行方向.在一定的条件下,算法收敛于所讨论问题的群体满意解.     

基于较优方案最大区别度的组合权重赋值法

现有多方案决策中的指标权重计算方法可能产生评价结果中较优方案不突出的难题,进而提出了一种新的方法——基于较优方案最大区别度的组合权重赋值法.方法可根据方案间区别度最大的原则将主观赋权法和客观赋权法中所确定的指标权重进行集结,综合考量待评方案,并建立多方案决策结果最大化和决策结果间方差最大化非线性优化模型,采用理想点法对具体的多目标规划问题进行求解.方法的运用有利于扩大备选方案之间的差距,进而突出较优方案,最后通过实例说明了该方法的优越性.     

两层多人多目标决策模型及其凸性

本文提出了四种一般性两层多人多目标决策模型及其最优解概念，它们适应于下层以不同已知信息提供给上层并涉及多个决策者不同偏好的两层多目标决策问题，研究了与这些模型相关的几种集值函数（包括下层有效前沿面，下层目标空间构成的集值函数和上层的两种复合目标集值函数）在各种意义下的凸性。     

多目标最优化的一种积分型实现算法

在文[1]中给出了求解多目标最优化的一种积分总极值的概念性算法．本文利用数论中的一致分布佳点集列，较为简便的得出了多目标最优化的积分总极值的实现算法和算法终止准则．并经过有关函数数值计算表明该算法是有效的，可用来求解多目标最优化问题的有效解．     

A multiobjective immune algorithm based on a multiple-affinity model

This paper presents a new multiobjective immune algorithm based on a multiple-affinity model inspired by immune system (MAM-MOIA). The multiple-affinity model builds the relationship model among main entities and concepts in multiobjective problems (MOPs) and multiobjective evolutionary algorithms (MOEAs), including feasible solution, variable space, objective space, Pareto-optimal set, ranking and crowding distance. In the model, immune operators including clonal proliferation, hypermutation and immune suppression are designed to proliferate superior antibodies and suppress the inferiors. MAM-MOIA is compared with NSGA-II, SPEA2 and NNIA in solving the ZDT and DTLZ standard test problems. The experimental study based on three performance metrics including coverage of two sets, convergence and spacing proves that MAM-MOIA is effective for solving MOPs.     

多目标决策的中心方法之统一探讨

该文从统一的角度研究了多目标决策的中心方法的结构及其收敛性质．提出了形式一般的、可采用三种曲线搜索规则的中心方法之算法模型并在很弱的条件下证明了其全局收敛性以此为基础．讨论了模型中的搜索方向等参量的取法，给出了两类可实现的算法．该文结果统一和推广了已有的单（多）目标决策的中心方法．数值结果表明该算法是有效的．     

Extensions of the multicriteria analysis with pairwise comparison under a fuzzy environment

Multicriteria decision-making (MCDM) problems often involve a complex decision process in which multiple requirements and fuzzy conditions have to be taken into consideration simultaneously. The existing approaches for solving this problem in a fuzzy environment are complex. Combining the concepts of grey relation and pairwise comparison, a new fuzzy MCDM method is proposed. First, the fuzzy analytic hierarchy process (AHP) is used to construct fuzzy weights of all criteria. Then, linguistic terms characterized by L–R triangular fuzzy numbers are used to denote the evaluation values of all alternatives versus subjective and objective criteria. Finally, the aggregation fuzzy assessments of different alternatives are ranked to determine the best selection. Furthermore, this paper uses a numerical example of location selection to demonstrate the applicability of the proposed method. The study results show that this method is an effective means for tackling MCDM problems in a fuzzy environment.     

多目标规划的极大熵方法

多目标规划的极大熵方法王雪华，秦学志（大连理工大学）ＴＨＥＭＡＸＩＭＵＭＥＮＴＲＯＰＹＭＥＴＨＯＤＦＯＲＭＵＬＴＩＯＢＪＥＣＴＩＶＥＰＲＯＧＲＡＭＭＩＮＧ￥ＷａｎｇＸｕｅ－ｈｕａ；ＱｉｎＸｕｅ－ｚｈｉ（ＤａｌｉａｎＵｎｉｖｅｒｓｉｔｙｏｆＴｅｃｈｎｏ...     

A subgradient method for multiobjective optimization

A method for solving quasiconvex nondifferentiable unconstrained multiobjective optimization problems is proposed in this paper. This method extends to the multiobjective case of the classical subgradient method for real-valued minimization. Assuming the basically componentwise quasiconvexity of the objective components, full convergence (to Pareto optimal points) of all the sequences produced by the method is established.     

Implementation aspects of interactive multiobjective optimization for modeling environments: the case of GAMS-NIMBUS

Interactive multiobjective optimization methods have provided promising results in the literature but still their implementations are rare. Here we introduce a core structure of interactive methods to enable their convenient implementation. We also demonstrate how this core structure can be applied when implementing an interactive method using a modeling environment. Many modeling environments contain tools for single objective optimization but not for interactive multiobjective optimization. Furthermore, as a concrete example, we present GAMS-NIMBUS Tool which is an implementation of the classification-based NIMBUS method for the GAMS modeling environment. So far, interactive methods have not been available in the GAMS environment, but with the GAMS-NIMBUS Tool we open up the possibility of solving multiobjective optimization problems modeled in the GAMS modeling environment. Finally, we give some examples of the benefits of applying an interactive method by using the GAMS-NIMBUS Tool for solving multiobjective optimization problems modeled in the GAMS environment.