随机网络瓶颈容量扩张相关机会规划模型

文章研究的问题为,在不确定环境中,怎样去增加网络中一组边的容量到一个指定的容量,以至于网络瓶颈扩张的费用不超过给定的总费用上限的概率尽可能的大.本文假定每一条边的单位扩张费用Wi是一个随机的变量,它服从一定的概率分布.带有随机单位扩张费用W的网络瓶颈容量扩张问题可以根据一些规则,列出它的相关机会规划模型的通用表达式.随后,本文将网络瓶颈容量算法、随机模拟方法和遗传算法合成在一起,设计出该问题的混合智能通用算法.最后,给出数值算例.     

3-Partitioning Problems for Maximizing the Minimum Load

The optimization versions of the 3-Partitioning and the Kernel 3-Partitioning problems are considered in this paper. For the objective to maximize the minimum load of the m subsets, it is shown that the MODIFIED LPT algorithm has performance ratios (3m – 1)/(4m – 2) and (2m – 1)/(3m – 2), respectively, in the worst case.     

目标函数为∑和max的双目标最短路问题:算法和复杂性

本文研究了一个双目标最短路问题。在该问题中,一个目标函数是∑形式,另一个目标函数是max形式。首先给出了一个时间复杂性为O(m²logn)的算法产生代表有效解集合。然后研究了∑和max的组合目标函数最短路问题,对动态问题和静态问题,分别给出了一个时间复杂性都为O(m²logn)的算法。最后在字典序最优解的意义下,本文给出了两个时间复杂性都为O(mlogn)的算法。     

横向并购初期固位策略销售服务网络结构优化

本文着眼于当今世界企业经营领域的前沿,对企业横向购并初期的销售服务网络的集成优化进行了深入研究,本文基于固定位置策略建立了优化模型,给出了模型的求解算法与计算复杂性。同时,本文以合并后5个销售服务中心30个客户为背景,给出了算法的仿真计算结果。     

Minimization of maximum lateness under linear deterioration

This paper considers a single-machine scheduling problem to minimize the maximum lateness. The processing time of each job is a linear function of the time when the job starts processing. This problem is known to be -hard in the literature. In this paper, we design a branch-and-bound algorithm for deriving exact solutions by incorporating several properties concerning dominance relations and lower bounds. These properties produce synergic effects in accelerating the solution finding process such that the algorithm can solve problems of 100 jobs within 1 min on average. To compose approximate solutions, we revise a heuristic algorithm available in the literature and propose several hybrid variants. Numerical results evince that the proposed approaches are very effective in successfully reporting optimal solutions for most of the test cases.     

一类供应链的Stackelberg主从对策问题研究

本文研究了供应链中的一般订货模式和协调模式,提出了一类供应链Stackelberg主从对策问题,卖方作为主方给出最小补充期策略,买方作为从方以最优库存策略响应。考虑一致价格折扣弥补买方的库存成本增加,以及买方的库存成本合理化,建立买方需求确定下的卖方成本优化模型。最后,应用遗传算法对石油分销系统Stackelberg主从对策问题离线仿真计算,得出Stackelberg主从对策均衡解。     

面向电子商务的基本遗传算法的Agent 谈判模型

探讨Agent 技术和遗传算法在电子商务网上谈判中的应用,为网上谈判的开展提供定量 和优化模型. 首先对三种基于Agent 的主流谈判模型进行比较研究;其次,从三个角度对谈判 模型进行分类,并确定基于Agent 技术的谈判系统的目标和特征;进一步研究基于遗传算法的 Agent 谈判模型,并对模型进行仿真实验,以证明模型的有效性. 该模型的特点是Agent 能在谈 判过程中学习和发展新的谈判策略.     

算法透明的困境及规制路径研究

算法决策技术的兴起推动了社会发展,同时也带来了算法黑箱、算法合谋、算法操纵等技术和社会风险,必须对算法进行规制以控制风险。算法透明是进行算法规制的前提和基础,由于技术和制度上的障碍,完全彻底的算法透明不现实也不合理,在具体场景中追求有限、适当的算法透明才是有意义的。在算法透明的落实和保障上,行政规制具有独特的优势,通过构建刚柔并济的行政规制体系、促进企业算法合规监管、推进算法备案制度、追究算法披露不当行为责任四项具体行政规制措施,监督和保障算法透明制度的运行,实现科技创新与社会安全之间的平衡与协调。     

Shared frailty model for recurrent event data with multiple causes

The topic of heterogeneity in the analysis of recurrent event data has received considerable attention recent times. Frailty models are widely employed in such situations as they allow us to model the heterogeneity through common random effect. In this paper, we introduce a shared frailty model for gap time distributions of recurrent events with multiple causes. The parameters of the model are estimated using EM algorithm. An extensive simulation study is used to assess the performance of the method. Finally, we apply the proposed model to a real-life data.     

Progressive multi-state models for informatively incomplete longitudinal data

Progressive multi-state models provide a convenient framework for characterizing chronic disease processes where the states represent the degree of damage resulting from the disease. Incomplete data often arise in studies of such processes, and standard methods of analysis can lead to biased parameter estimates when observation of data is response-dependent. This paper describes a joint analysis useful for fitting progressive multi-state models to data arising in longitudinal studies in such settings. Likelihood based methods are described and parameters are shown to be identifiable. An EM algorithm is described for parameter estimation, and variance estimation is carried out using the Louis’ method. Simulation studies demonstrate that the proposed method works well in practice under a variety of settings. An application to data from a smoking prevention study illustrates the utility of the method.