基于改进离散粒子群算法的炼钢连铸最优浇次计划

提出了浇次数未知的最优浇次计划模型. 在分析该模型求解困难的基础上, 提出了用伪旅行商表示该模型的方法. 针对离散粒子群优化具有收敛速度、精度低, 但能充分利用各粒子的局部最优值和全局最优值信息的特点,而序列倒置算子具有收敛速度和精度较高, 但学习具有盲目性的特点, 结合二者优点, 提出了一种基于序列倒置的改进离散粒子群优化算法. 实验研究表明, 该算法与普通离散粒子群优化算法相比, 不论是收敛速度和还是求解精度都有了较大提高. 基于该改进算法求解最优浇次计划模型的研究表明: 所提伪旅行商问题模型非常适合用于组浇模型描述. 应用实际生产数据的计算表明该模型及其求解方法均非常有效.     

多目标多维自反馈模糊决策模型

针对多目标的决策问题,依据模糊识别理论提出一种多目标多维自反馈模糊决策模型.首先根据给定的目标初始权重计算加权综合决策值;然后利用单指标模糊识别方法计算加权综合决策值的模糊划分;最后依据成因分析并用决策值的模糊划分,计算出目标的权重.重复上述计算过程,可得到满足精度要求的加权综合决策值及其模糊划分,根据计算结果可判定决策类别和优劣排序.炼钢企业评价决策实例表明,所提出的模糊决策模型是有效的.     

基于工作过程导向的“网页设计与制作”课程教学改革研究

本文阐述了基于工作过程的高职网页设计课程的改革思路,运用先进的教学理念,以行动体系为依托,以职业活动为主线。以项目任务驱动为教学形式的"基于工作过程导向"模式对课程教学改革进行了研究与实践。     

On group decision making with four formats of incomplete preference relations

In this paper, a new approach is proposed to solve group decision making (GDM) problems where the preference information on alternatives provided by decision makers (DMs) is represented in four formats of incomplete preference relations, i.e., incomplete multiplicative preference relations, incomplete fuzzy preference relations, incomplete additive linguistic preference relations, incomplete multiplicative linguistic preference relations. In order to make the collective opinion close each decision maker’s opinion as near as possible, an optimization model is constructed to integrate the four different formats of incomplete preference relations and to compute the collective ranking values of the alternatives. The ranking of alternatives or selection of the most desirable alternative(s) is directly obtained from the derived collective ranking values. A numerical example is also used to illustrate the applicability of the proposed approach.     

An inexact fuzzy-queue programming model for environmental systems planning

In this study, an inexact fuzzy-queue programming (IFQP) model is developed for municipal solid waste (MSW) management under uncertainty, where fuzzy queue (FQ) model is introduced into the interval-fuzzy linear programming (IFLP) framework. The proposed IFQP model can not only handle uncertainties that are presented in terms of fuzzy sets and discrete intervals, but also reflect the influence of FQ in decision-making problems. Moreover, it can help quantify the satisfaction degrees of the system cost and constraints under uncertainty. It improves upon the existing optimization model with advantages in data availability, uncertainty reflection and result analysis. In its solution process, the model is transformed into two deterministic submodels based on an interactive algorithm. Interval solutions which are stable in the decision space can be obtained by solving the two submodels sequentially. The developed model is applied to a case of long-term planning of MSW management systems to demonstrate its applicability. It can effectively reflect dynamic, interactive, and uncertain characteristics of municipal waste management systems. The decision variable solutions provide optimal schemes for waste flow allocation corresponding to lower and upper bounds of system cost. The results indicate that reasonable solutions have been generated. They are helpful for supporting: (i) decision making or justification of waste-allocation patterns of MSW management system, and (ii) in-depth analysis of tradeoffs among system cost, satisfaction degree, and environmental constraint under uncertainty.     

基于CBR和MADM的多Agent推荐系统

为解决目前基于CBR的推荐系统只考虑属性值全部为精确或全部为非精确数据的情况,提出一种基于MADM的多Agent推荐系统框架。在考虑了属性分类的基础上设计了基于距离的混合数据类型的相似性度量算法及TOPSIS多属性决策方法,设计了该系统各组成部分功能、结构和流程。模拟算例演示了案例推理及多属性决策在本系统的应用过程,结果表明该系统有较好的实用性。     

基于参考点和投票规则的多目标粒子群优化群体决策

针对巨量可选方案的群体决策问题,提出了一个新的基于参考点和投票规则的多目标粒子群优化算法。该算法把个体与参考点的支配关系或者距离作为一个重要因素,在选择引导者的锦标赛方法,局部最优更新规则,以及外部种群档案剪枝规则中都嵌入了基于支配关系或距离因素的投票规则,以找到群体决策解,并且提高搜索效率。仿真结果表明该算法有效。     

Several multi-criteria programming methods for classification

In this paper, we propose a general optimization-based model for classification. Then we show that some well-known optimization-based methods for classification, which were developed by Shi et al. [Data mining in credit card portfolio management: a multiple criteria decision making approac. In: Koksalan M, Zionts S, editors. Multiple criteria decision making in the new millennium. Berlin: Springer; 2001. p. 427–36] and Freed and Glover [A linear programming approach to the discriminant problem. Decision Sciences 1981; 12: 68–79; Simple but powerful goal programming models for discriminant problems. European Journal of Operational Research 1981; 7: 44–60], are special cases of our model. Moreover, three new models, MCQP (multi-criteria indefinite quadratic programming), MCCQP (multi-criteria concave quadratic programming) and MCVQP (multi-criteria convex programming), are developed based on the general model. We also propose algorithms for MCQP and MCCQP, respectively. Then we apply these models to three real-life problems: credit card accounts, VIP mail-box and social endowment insurance classification. Extensive experiments are done to compare the efficiency of these methods.     

An e-commerce performance assessment model: Its development and an initial test on e-commerce applications in the retail sector of China

We developed a performance assessment model for e-commerce; it included indicators, indicator weights, and evaluation methods. The model has seven methods of assessing e-commerce performance and uses four criteria to compare and select the appropriate one for a particular situation. This model was tested in the retail sector of China. According to the data collected from 70 Chinese retailers, 16 indicators of e-commerce performance consisted of four constructs: marketing and sales, customer service, supply chain efficiency, and financial performance. The indicators for those constructs provide a comprehensive measurement of performance. Then weights were assigned for each indicator using a majority aggregation method. Comparison of the results from seven evaluation methods showed that discordance analysis and simple additive weighting were the best evaluation methods for the enterprises we had sampled.     

Semantic Web Constraint Language and its application to an intelligent shopping agent

Semantic Web society was initially focused only on data, but then gradually moved toward knowledge. If a vision of the Semantic Web is to enhance humans' decision-making assisted by machines, a missing but important part is knowledge about constraints on data and concepts represented by ontology. This paper proposes a Semantic Web Constraint Language (SWCL) based on OWL, and shows its effectiveness in representing and solving an internet shopper's decision-making problems by implementing a shopping agent in the Semantic Web environment.