时间窗口约束下基于改进蚁群算法的协同制造调度研究

与传统调度模式不同，协同制造模式下企业之间的调度模式极其复杂。协同企业间的加工工序路线并不固定，且不同类型产品具有不同的加工路线网络。为此本文针对平衡型、瓶颈型、跳跃型、混合型四类具有典型特点的协同制造网络G_p进行分析和设计；考虑制造企业同类产品合并加工策略，构建基于连续加工量的分段生产成本函数；通过设计合理的订单最早交货时间和最晚交货时间，对订单交货进行时间窗口约束，并在此基础上构建了由制造商生产成本W_c^m、订单等待W_s^k（Q_k， T'_k）和提前完工库存成本W_s^k（Q_k， T″_k）、延期惩罚成本构成W_l^k（Q_k， T'″_k）的目标函数。为求解该模型，创新性将蒙特卡洛思想引入蚁群算法，提高蚂蚁选择合理性，避免局部最优；同时，采用移动窗口[min， max]奖励机制，并且对信息素奖励乘以平衡系数k（N）提高奖励可信度，加快搜索速度并提高求解性能。仿真结果表明，本文构建调度模型合理，可以获得优化的调度结果；同时，本文提出的蚁群改进寻优算法具有良好的求解速度和收敛性，算法具有较好的稳定性。     

Desires matter! Desired attitudes predict behavioural intentions in people who think abstractly: the case of eating products without added salt / ¡Los deseos importan! Las actitudes deseadas predicen las intenciones de comportamiento en las personas que piensan de modo abstracto: El caso del consumo de alimentos sin sal añadida

Introduction. Previous research supports that congruence in the construal level between a person’s mindset and predictors enhanced the strength of predictions. Because desired attitudes are more abstract than actual attitudes, we expected that desired attitudes would better predict behavioural intentions in people who present an abstract style of thinking. Objective. We tested this matching effect between desired attitudes and abstractness by measuring the construal level as a person’s base-rate tendency. Method. Participants (N = 105) reported their past experience and actual and desired attitudes towards eating products without added salt and their behavioural intentions. To classify participants according to an abstract or a concrete way of thinking, their first thought was coded using the linguistic category model (LCM). Results. The simple slopes analysis showed that desired attitudes significantly influenced behavioural intentions for participants with an abstract way of thinking. Conclusion. Our results support the relevance of desired attitudes in terms of behavioural predictions and extend the role of the construal level in the prediction and promotion of desirable but demanding behaviour in the framework of individual differences.     

A statistical multivariable optimization method using improved orthogonal algorithm based on large data

Multivariable optimization under large data environment concerns with how to reliably obtain a set of optimization results from a mass of data that influence the object function complexly. This is an important issue in statistical calculation because the complexity between variable parameters leads to repeated statistical calculation analysis and a significant amount of data waste. A statistical multivariable optimization method using improved orthogonal algorithm based on large data is proposed. Considering the optimization problem with multi-parameters under large data environment, a multi-parameter optimization model used for improved orthogonal algorithm is established based on large data. Furthermore, an extensive simulation study on temperature field distribution of anti-/de-icing component was conducted to verify the validity of the statistical calculation analysis optimization method. The optimized temperature field distribution meets the anti-/de-icing requirements through numerical simulation. Simulation results show that the optimization effect is more evident and accurate than the non-optimized temperature distribution with the optimized results of the proposed method. Results verify the effectiveness of the proposed method.     

Lower bounds for confidence coefficients for confidence intervals for finite population quantiles

Assuming stratified simple random sampling, a confidence interval for a finite population quantile may be desired. Using a confidence interval with endpoints given by order statistics from the combined stratified sample, several procedures to obtain lower bounds (and approximations for the lower bounds) for the confidence coefficients are presented. The procedures differ with respect to the amount of prior information assumed about the var-iate values in the finite population, and the extent to which sample data is used to estimate the lower bounds.     

Improved pretest nonparametric estimation in a multivariate regression model

Shrinkage pretest nonparametric estimation of the location parameter vector in a multivariate regression model is considered when nonsample information (NSI) about the regression parameters is available. By using the quadratic risk criterion, the dominance of the pretest estimators over the usual estimators has been investigated. We demonstrate analytically and computationally that the proposed improved pretest estimator establishes a wider dominance range for the parameter under consideration than that of the usual pretest estimator in which it is superior over the unrestricted estimator.     

民主与法治:财政支出监督中的问题与对策

财政支出的监督是宪法和法律规定的一项重要的法律制度,监督是财政得以正确实施的保护伞。文章分析了当前我国财政监督法律制度的缺失,提出相应的对策,阐明了财政支出监督的重要性和紧迫性。     

网络调查的概念整合模型研究

网络调查作为一种方便易用、目标群明确、成本低、灵活性强的调查方法，在电子商务等领域的新产品开发、服务质量研究和客户保持中具有潜在的实用价值。但是，网络调查的回复率呈现逐年下降趋势。虽然国内外学者对不回复或不愿参与自填问卷调查的原因进行了大量的研究，但这些研究多数是从某一角度展开的，很少有研究者解决了在线环境下的不回复问题。本文在考察了现有关于网络调查不回复问题的文献基础上，基于计划行为理论（TPB）模型，提出了网络调查的概念整合模型，该模型综合了有关网络调查中不回复原因的研究成果，可用于分析在线环境下不回复问题，为完全解决网络调查完全不回复问题奠定了基础。     

Improved ridge estimators in a linear regression model

In this paper, the notion of the improved ridge estimator (IRE) is put forward in the linear regression model y=X β+e. The problem arises if augmenting the equation 0=c′α+ε instead of 0=C α+? to the model. Three special IREs are considered and studied under the mean-squared error criterion and the prediction error sum of squares criterion. The simulations demonstrate that the proposed estimators are effective and recommendable, especially when multicollinearity is severe.     

东部三大经济区域产业升级能力评价研究

我国东部三大经济区域的经济已经发展到一定阶段,产业升级已成为当前的主要任务。文章建立了产业升级能力的评价指标体系,并以2008年的相关统计数据为依据,采用改进的TOPSIS方法计算了东部三大经济区域的产业升级能力,然后对其进行比较分析,最后给出提升东部三大经济区域产业升级能力的对策与建议。