An augmented approach to the desirability function

The desirability function is widely used in the engineering field to tackle the problem of optimizing multiple responses simultaneously. This approach does not account for the variability in the predicted responses and minimizing this variability to have narrower prediction intervals is desirable. We propose to add this capability in the desirability function and also incorporate the relative importance of optimizing the multiple responses and minimizing the variances of the predicted responses at the same time. We show that the benefits of our augmented approach using two real data sets by comparing our solutions with those obtained from the desirability approach. In particular, it is shown that our approach offers greater flexibility and the solutions can reduce the variances of all the predicted responses resulting in narrower prediction intervals.     

灰色GM(1,1)幂模型初始条件的组合优化

针对GM(1,1)幂模型求解初始条件的优化问题,提出一种基于原始序列新旧信息的线性组合优化方法.在模拟误差平方和最小化的目标下,构建初始条件组合权重的优化模型,给出最优组合权重的解析式.最后以中国高中升学率的数据为例,验证了此优化模型的有效性和优越性.结果表明初始条件优化方法能够有效地平衡新旧信息的权重,并提高GM(1,1)幂模型的模拟和预测精度.     

新型农村合作医疗的参合补助——悖论及路径优化

新农合的财政补助水平与农民需求存在较大缺口,客观上需要政府提高补助水平。但由于农民有限理性的存在,在个人缴费在先且与财政补助同比增长的制度安排下,形成了农民既需要参合补助,又不愿因增加个人缴费以获得补助的悖论,且此情况会因制度供给缺陷而激化。因此,需要对新农合的参合补助路径进行优化。设计灵活的参合缴费模式,调整农民缴费与政府补助的增长幅度,提高农民医疗补偿的比例都是可行的选择。     

Probabilistic graph-coloring in bipartite and split graphs

We revisit in this paper the stochastic model for minimum graph-coloring introduced in (Murat and Paschos in Discrete Appl. Math. 154:564–586, 2006), and study the underlying combinatorial optimization problem (called probabilistic coloring) in bipartite and split graphs. We show that the obvious 2-coloring of any connected bipartite graph achieves standard-approximation ratio 2, that when vertex-probabilities are constant probabilistic coloring is polynomial and, finally, we propose a polynomial algorithm achieving standard-approximation ratio 8/7. We also handle the case of split graphs. We show that probabilistic coloring is NP-hard, even under identical vertex-probabilities, that it is approximable by a polynomial time standard-approximation schema but existence of a fully a polynomial time standard-approximation schema is impossible, even for identical vertex-probabilities, unless P=NP. We finally study differential-approximation of probabilistic coloring in both bipartite and split graphs. Part of this research has been performed while the second author was with the LAMSADE on a research position funded by the CNRS.     

An extension of the relaxation algorithm for solving a special case of capacitated arc routing problems

In this paper, we propose an exact method for solving a special integer program associated with the classical capacitated arc routing problems (CARPs) called split demand arc routing problems (SDARP). This method is developed in the context of monotropic programming theory and bases a promising foundation for developing specialized algorithms in order to solve general integer programming problems. In particular, the proposed algorithm generalizes the relaxation algorithm developed by Tseng and Bertsekas (Math. Oper. Res. 12(4):569–596, 1987) for solving linear programming problems. This method can also be viewed as an alternative for the subgradient method for solving Lagrangian relaxed problems. Computational experiments show its high potential in terms of efficiency and goodness of solutions on standard test problems.     

Graph coloring by multiagent fusion search

A multiagent fusion search is presented for the graph coloring problem. In this method, each of agents performs the fusion search, involving a local search working in a primary exploitation role and a recombination search in a navigation role, with extremely limited memory and interacts with others through a decentralized protocol, thus agents are able to explore in parallel as well as to achieve a collective performance. As the knowledge components implemented with available structural information and in formalized forms, the Quasi-Tabu local search and grouping-based recombination rules are especially useful in addressing neutrality and ruggedness of the problem landscape. The new method has been tested on some hard benchmark graphs, and has been shown competitive in comparison with several existing algorithms. In addition, the method provides new lower bound solutions when applied to two large graphs. Some search characteristics of the proposed method is also discussed.     

汶川特大地震灾后社区心理援助的统筹优选模式

汶川特大地震使灾区城镇和农村原有的社区基本被破坏甚至毁灭,通过对灾后社区展开问卷调查和访谈,运用SPSS统计分析软件,找出灾后社区心理援助的关键问题。在以人为本的科学发展观的统领下,依据统筹优选的思想与方法,以在最短的时间内投入最少精力,运用最有效的方法取得最佳援助效果为目的,分析灾后社区心理援助的解决思路,构建灾后社区心理援助的基本框架,提出灾后社区心理援助的统筹优选模式。该模式包括灾后心理评估体系和灾后社区心理援助过程2个方面,前者由灾后心理评估和援助效果评估2个部分组成;后者包括初期心理援助、中期心理援助和长期心理援助3个阶段,分别从援助主客体、援助内容和援助方法来进行分析研究,实现对地震灾后社区的心理援助。     

不确定需求环境下多级库存系统优化与协调模型研究

论文首先将模糊随机变量扩展为混合随机变量,并用来描述不确定需求.然后对多级单周期库存系统在模糊随机和混合随机需求环境下的优化与协调问题作了研究,提出了通过集成库存管理使库存系统整体收益期望值最大化的优化模型和协调合作伙伴利益的数量折扣契约模型,并根据遗传算法理论和计算机模拟技术设计了求解模型的智能算法.最后通过实例对模型进行了仿真分析.     

基于银行授信额度的Max-NPV项目调度问题研究

本文对基于银行授信额度的Max-NPV项目调度问题进行研究.首先界定研究的假设条件并对文中所用到的符号进行定义;随后采用基于事件的研究方法构建了问题的整数规划优化模型;鉴于问题的NP-hard属性,设计了双层模拟退火搜索循环嵌套的启发式求解算法;最后对一个算例进行了求解分析,并讨论了银行授信额度及客户支付比例对项目收益的影响.结果表明:随着银行授信额度的提高,承包商安排项目进度自由度的增加使得其净现值得到改善,在支付比例较低的条件下项目完成时间也随之提前;当客户支付比例提高时,项目净现值单调上升,而项目完成时间呈先提前后延迟的变化趋势.