Inverse Combinatorial Optimization: A Survey on Problems, Methods, and Results

Given a (combinatorial) optimization problem and a feasible solution to it, the corresponding inverse optimization problem is to find a minimal adjustment of the cost function such that the given solution becomes optimum.Several such problems have been studied in the last twelve years. After formalizing the notion of an inverse problem and its variants, we present various methods for solving them. Then we discuss the problems considered in the literature and the results that have been obtained. Finally, we formulate some open problems.     

A General Formula for Valuing Defaultable Securities

Previous research has shown that under a suitable no‐jump condition, the price of a defaultable security is equal to its risk‐neutral expected discounted cash flows if a modified discount rate is introduced to account for the possibility of default. Below, we generalize this result by demonstrating that one can always value defaultable claims using expected risk‐adjusted discounting provided that the expectation is taken under a slightly modified probability measure. This new probability measure puts zero probability on paths where default occurs prior to the maturity, and is thus only absolutely continuous with respect to the risk‐neutral probability measure. After establishing the general result and discussing its relation with the existing literature, we investigate several examples for which the no‐jump condition fails. Each example illustrates the power of our general formula by providing simple analytic solutions for the prices of defaultable securities.     

基于DEA理论的ANP/BOCR方案评价值综合集成新方法

网络分析法(ANP)是一种能够有效处理复杂决策问题的多准则决策方法。然而现有ANP文献在对收益、机会、成本、风险(统称为BOCR)评价值综合集成时会因评价值之间的不匹配而可能得出错误的方案排序结果和绩效表示。为克服上述缺陷,本文基于数据包络分析理论提出一种新的针对ANP/BOCR评价值的综合集成方法,使用摆幅置权区间估计方式反映出了决策者在判断BOCR相对权重时所面临的不精确性和模糊性。实例验证结果表明,所提方法对BOCR评价值的处理更符合实际情况。     

基于多种不确定性参数分布的U-GERT网络模型及其应用研究

针对随机网络研究中活动参数的分布是不确定信息的情况,本文提出了不确定信息的GERT网络模型,并利用信号流图原理研究了不确定信息的GERT网络仿真算法;研究了不确定变量GERT网络的矩母函数的构造,并对其重要的性质做了详细的探讨;最后通过算例仿真,验证本文提出的不确定信息的GERT网络模型及其仿真算法能够有效的解决现实生活中不确定信息对GERT网络参数的影响,说明模型与算法正确可行。     

面向价值网络的企业协同竞争博弈模型研究

运用演化博弈理论的方法,分析价值网络模式下企业的协同竞争机制,构建企业主体间协同竞争的演化博弈模型,指出价值网络模式下企业协同竞争行为的博弈过程及特点,揭示出系统的初始状态、发展阶段及利益分配机制对演化博弈过程的影响机理。     

基于GERT随机网络的废弃回收预测模型研究

在阐述回收处理业务流程的基础上,分析其不确定性;运用随机网络系统模型的相关理论构建GERT网络模型,探讨产品回收再制造零部件和可再生材料的预测模型。该模型既可以预测出废弃产品返回数量、回收处理过程中的再造零部件和可再生材料的比例和数量,又可以预测出它们的期望返回时间。最后,以打印机的回收再制造为例,对模型进行了实际应用。     

网络能力、资源获取与新企业绩效关系实证研究

网络能力是在网络导向驱动下,利用关系技巧和合作技巧进行一系列网络构建和网络管理活动,以实现资源获取目标的能力.在中国转型经济时期,网络能力对于新企业克服资源约束,实现生存和成长具有重要作用.拓展了网络能力的理论内涵,将网络能力划分为网络导向、网络构建和网络管理三个维度,建立了网络能力、资源获取与新创企业绩效关系模型,以322家新企业为样本进行实证分析.研究结果表明,网络导向对网络构建和网络管理具有显著正影响,网络构建和网络管理对知识资源获取和运营资源获取具有正影响,知识资源与新企业绩效显著正相关,知识资源获取对运营资源获取具有正影响.研究结论还表明运营资源对新企业绩效无显著影响,但知识资源可以加强两者之间关系,说明新企业只有具备很强的资源管理能力才能将运营资源转化为企业绩效.     

非线性需求下具有网络外部性的二级歧视定价研究

研究了非线性需求函数条件下产品存在网络外部性时,垄断企业采用对需求区间分段定价的方法进行二级歧视定价的策略。首先分析了单阶段垄断企业二级价格歧视的静态定价策略,接着给出了在一个较长时期内垄断企业分两阶段进行二级歧视的动态定价策略。结果表明网络外部性不影响最优需求区间分段单调递增的性质,但价格随网络外部性的增强而相应提高,且第一阶段的价格高于第二阶段的贴现值。     

基于理性提前偿付的住房抵押贷款证券定价研究

在分析MBS定价的影响因素以及比较结构化模型与简化形式模型定价方法的基础上,考虑模型的稳健性和可操作性,本文利用简化方法中的Schwartz和Torous定价模型,以建元2007-1RMBS作为研究对象,模拟出BDT利率模型下的利率期限结构,再结合提前还款模型中的PSA法确定贷款现金流,进而确定期权调整价差OAS,构建了适用于我国的MBS定价模型。     

Robustness of Risk Maps and Survey Networks to Knowledge Gaps About a New Invasive Pest

In pest risk assessment it is frequently necessary to make management decisions regarding emerging threats under severe uncertainty. Although risk maps provide useful decision support for invasive alien species, they rarely address knowledge gaps associated with the underlying risk model or how they may change the risk estimates. Failure to recognize uncertainty leads to risk‐ignorant decisions and miscalculation of expected impacts as well as the costs required to minimize these impacts. Here we use the information gap concept to evaluate the robustness of risk maps to uncertainties in key assumptions about an invading organism. We generate risk maps with a spatial model of invasion that simulates potential entries of an invasive pest via international marine shipments, their spread through a landscape, and establishment on a susceptible host. In particular, we focus on the question of how much uncertainty in risk model assumptions can be tolerated before the risk map loses its value. We outline this approach with an example of a forest pest recently detected in North America, Sirex noctilio Fabricius. The results provide a spatial representation of the robustness of predictions of S. noctilio invasion risk to uncertainty and show major geographic hotspots where the consideration of uncertainty in model parameters may change management decisions about a new invasive pest. We then illustrate how the dependency between the extent of uncertainties and the degree of robustness of a risk map can be used to select a surveillance network design that is most robust to knowledge gaps about the pest.