基于多目标规划的中国可持续发展模式优化研究

本文以人口(Population)、资源(Resource)、经济(Economy)、环境(Environment)和科技(Science & Technolo gy)为核心,构造了PREEST系统模型。以PREEST系统为对象,运用主成分分析法对1987-2001年度中国的可持续发展水平进行了综合评价;借助多目标规划理论,构建了中国可持续发展多目标集成模型,并以"十五"计划纲要为基准,开展了中国可持续发展规划研究的实证分析。在此基础上,通过对"十五"期间中国可持续发展传统模式和规划模式的对比分析,就中国人口、资源、经济、环境和科技等领域的协调发展提出了政策建议。     

Comments on the Paper: Attacking the Market Split Problem with Lattice Point Enumeration

We present a few comments on the paper Attacking the market split problem with lattice point enumeration by A. Wasserman, published in Journal of Combinatorial Optimization, vol. 6, pp. 5–16, 2002.     

多媒体教学的利弊分析及相应对策

多媒体教学以其题材丰富形象、形式活泼多样、课堂信息量大、节省板书时间、可以大范围授课等优势 ,确立了在现代教学手段中的主导地位。但现阶段的多媒体教学还处在一个尚待继续发展的不成熟阶段 ,存在着一些需要改进之处。本文结合对计算机高级程序设计语言的教学 ,分析了多媒体教学的利弊 ,探讨了多媒体教学应用中出现的问题 ,并提出了相应的改进对策     

On Inverse Problems of Optimum Perfect Matching

As far as we know, for most polynomially solvable network optimization problems, their inverse problems under l ₁ or l norm have been studied, except the inverse maximum-weight matching problem in non-bipartite networks. In this paper we discuss the inverse problem of maximum-weight perfect matching in a non-bipartite network under l ₁ and l norms. It has been proved that the inverse maximum-weight perfect matching under l norm can be formulated as a maximum-mean alternating cycle problem of an undirected network, and can be solved in polynomial time by a binary search algorithm and in strongly polynomial time by an ascending algorithm, and under l ₁ norm it can be solved by the ellipsoid method. Therefore, inverse problems of maximum-weight perfect matching under l ₁ and l norms are solvable in polynomial time.     

新时期思想政治教育的目标模式

党的思想政治教育的根本目的是为无产阶级解放事业服务 ,它在不同时期表现为不同的培养目标 ,而对培养目标的规定又展开为具体的目标模式。在革命战争年代 ,思想政治教育的目标是培养革命者 ,其具体模式以毛泽东为陕北公学的题词为代表 ;建国后 ,思想政治教育的目标是培养无产阶级革命事业的接班人和社会主义事业建设者 ,其具体模式以毛泽东关于“两有”的表述为代表 ;在新时期 ,思想政治教育的目标是培养社会主义事业建设者和接班人 ,目标模式是邓小平提出的“四有”新人。这一目标模式的成熟形态具有全面性、重点性、层次性和总体性特点。江泽民在新形势下丰富发展了这一目标模式     

The densest <Emphasis Type="Italic">k</Emphasis>-subgraph problem on clique graphs

The Densest k-Subgraph (DkS) problem asks for a k-vertex subgraph of a given graph with the maximum number of edges. The problem is strongly NP-hard, as a generalization of the well known Clique problem and we also know that it does not admit a Polynomial Time Approximation Scheme (PTAS). In this paper we focus on special cases of the problem, with respect to the class of the input graph. Especially, towards the elucidation of the open questions concerning the complexity of the problem for interval graphs as well as its approximability for chordal graphs, we consider graphs having special clique graphs. We present a PTAS for stars of cliques and a dynamic programming algorithm for trees of cliques. M.L. is co-financed within Op. Education by the ESF (European Social Fund) and National Resources. V.Z. is partially supported by the Special Research Grants Account of the University of Athens under Grant 70/4/5821.     

Robust portfolio planning in the presence of market anomalies

In this study, a short-term portfolio modeling formulation is developed using existing anomalies as a single determinant for daily Istanbul Stock Exchange National 100 Composite Index (ISE) and US dollars (USD) returns in a Robust optimization (RO) framework. Using anomalies in planning within an RO framework establishes a balance between risk seeking and risk averse behaviors, as generating profit from anomalies is risky and RO enables to settle down the extreme risk seeking behavior. Applications of the model using various data sets result in real profit generation such that terminal wealth figures increase considerably more than Wholesale Price Index (WPI). This study demonstrates that RO is a viable approach to make use of anomaly information for short-term profits.     

An interactive three-stage model for mutual funds portfolio selection

The aim of this work is to be a useful instrument for helping finance practitioners on the selection of suitable mutual fund portfolios. The portfolio selection problem is characterized by imprecision and/or vagueness inherent in the required data and more generally, in the context where investors have to make decisions. In order to mitigate these problems, a three stage model has been proposed based on a multi-index model and considering several market scenarios described in an imprecise way by an expert. The proposed fuzzy model allows the Decision Maker to select, by means of an outranking method, a suitable portfolio taking into account the uncertainty related to the market scenarios and the imprecision and/or vagueness associated with the model data.     

The wireless network jamming problem

In adversarial environments, disabling the communication capabilities of the enemy is a high priority. We introduce the problem of determining the optimal number and locations for a set of jamming devices in order to neutralize a wireless communication network. This problem is known as the wireless network jamming problem. We develop several mathematical programming formulations based on covering the communication nodes and limiting the connectivity index of the nodes. Two case studies are presented comparing the formulations with the addition of various percentile constraints. Finally, directions of further research are addressed.     

利用和声分散搜索算法解决动态共乘的乘客选择研究

动态共乘作为一种配合解决城市交通出行难题的新模式近年来引起了人们越来越多的关注，然而在较大范围内选择合适的乘客，以便获得最佳的综合服务效果却具有相当大的挑战性。本文正是针对这一问题，建立了以乘客效用最大化和司机总行程最短为目标函数，以满足司机与乘客的时间要求和司机参与约束为限制条件的多目标0-1规划共乘模型，用于帮助司机选择最合适的乘客。根据该模型的特点，构造了加入了分散搜索机制的新的和声搜索算法。在仿真实验时，针对司机和乘客效用的两种产生方式，在较大规模的路网环境下利用该算法分别对模型进行了求解，得到了Pareto最优解集。仿真结果不仅表明了模型的合理性和算法的可行性，而且还指出基于效用函数可以发现更多合适的潜在乘客。最后，通过与文献中其它算法的对比进一步展示了本文算法的有效性。