考虑决策者失望规避的供应链协同绿色创新动态优化与协调研究

针对决策者存在失望规避行为且产品绿色水平具有动态变化特征的情形,基于失望理论,运用微分博弈的方法研究了供应链协同绿色创新动态优化与协调问题,探讨了供应链成员失望规避程度对绿色创新决策及供应链绩效的影响,并提出双向成本分担契约对供应链进行协调。结果表明,供应链成员是否选择协同绿色创新及产品的绿色水平均与成员的失望规避程度密切相关;分散式决策下,若制造商选择分担供应商部分绿色创新成本,其分担比例与制造商失望规避程度负相关,与供应商失望规避程度正相关;集中式决策下,产品绿色水平、成员绿色创新水平及效用现值均高于协调前分散系统中的对应值;在一定条件下,双向成本分担契约的设计与实施,能有效提升供应链成员效用现值,实现供应链协调。     

基于后悔理论的灰色应急决策方案动态调整方法

突发事件发展具有可变性、动态性、随机性等特点,这要求决策者能根据实际情况及时调整应急方案,在此过程中决策者往往表现出“有限理性”的心理特征。针对以上情形,提出一种基于后悔理论的决策方法,以解决不确定环境下考虑决策者心理因素的应急方案动态调整问题。该方法首先描述分析了基于灰数信息的应急调整方案的生成过程;然后从后悔规避的视角构造了调整方案集关于处置效果、调整成本、应对损失三方面的灰色感知效用矩阵;进一步,用转移概率矩阵预测突发事件的演化概率,计算各调整方案的灰色综合感知效用值以选出最佳调整方案;最后,通过实例验证了该方法的可行性和有效性。结果表明,该方法贴近决策实际、具有较强的实用性;能够为应急决策的方案调整问题提供方法指导和理论支持。     

考虑风险规避的供应链融资与信用保险组合模型研究

针对供应链的资金约束问题,考虑了由一个资金约束的零售商、资金充足的供应商、风险规避型银行以及保险公司组成的供应链融资系统,分别构建了风险规避型银行融资模型以及银行融资与信用保险的组合模型,给出了两种模型中供应链融资系统成员的最优决策。研究表明:与传统风险规避型的银行融资模型相比,银行融资与信用保险的组合模型能够有效地增加零售商的融资规模,并降低银行的损失风险,从而信用保险能够给整个供应链融资系统带来严格帕累托改进。最后,通过数值算例说明了研究结论的有效性。     

Greedy heuristics with regret, with application to the cheapest insertion algorithm for the TSP

We consider greedy algorithms that allow partial regret. As an example we consider a variant of the cheapest insertion algorithm for the TSP. Our numerical study indicates that in most cases it significantly reduces the relative error, and the added computational time is quite small.     

Two-person insurance negotiation

This paper considers a risk-neutral insurer and a risk-averse individual who bargain over the terms of an insurance contract. The Core and the Nash solution to this bargaining game are characterized. It is shown that the insurer's expected profit is higher when bargaining with a more risk-averse individual.     

Approximation of min–max and min–max regret versions of some combinatorial optimization problems

This paper investigates, for the first time in the literature, the approximation of min–max (regret) versions of classical problems like shortest path, minimum spanning tree, and knapsack. For a constant number of scenarios, we establish fully polynomial-time approximation schemes for the min–max versions of these problems, using relationships between multi-objective and min–max optimization. Using dynamic programming and classical trimming techniques, we construct a fully polynomial-time approximation scheme for min–max regret shortest path. We also establish a fully polynomial-time approximation scheme for min–max regret spanning tree and prove that min–max regret knapsack is not at all approximable. For a non-constant number of scenarios, in which case min–max and min–max regret versions of polynomial-time solvable problems usually become strongly NP-hard, non-approximability results are provided for min–max (regret) versions of shortest path and spanning tree.     

Convergence of Utility Indifference Prices to the Superreplication Price

A discrete-time financial market model is considered with a sequence of investors whose preferences are described by concave strictly increasing functions defined on the positive axis. Under suitable conditions, we show that the utility indifference prices of a bounded contingent claim converge to its superreplication price when the investors’ absolute risk-aversion tends to infinity.     

一类无穷区间的倒向随机微分方程及其应用

本文讨论了一类基于无穷区间的倒向随机微分方程解的存在唯一性及其性质. 由方程解定义一类非线性g-期望, 并讨论其在经济金融中的应用.     

On cross-risk vulnerability

We introduce the notion of cross-risk vulnerability to generalize the concept of risk vulnerability introduced by Gollier and Pratt [Gollier, C., Pratt, J.W. 1996. Risk vulnerability and the tempering effect of background risk. Econometrica 64, 1109–1124]. While risk vulnerability captures the idea that the presence of an unfair financial background risk should make risk-averse individuals behave in a more risk-averse way with respect to an independent financial risk, cross-risk vulnerability extends this idea to the impact of a non-financial background risk on the financial risk. It provides an answer to the question of the impact of a background risk on the optimal coinsurance rate and on the optimal deductible level. We derive necessary and sufficient conditions for a bivariate utility function to exhibit cross-risk vulnerability both toward an actuarially neutral background risk and toward an unfair background risk. We also analyze the question of the sub-additivity of risk premia and show to what extent cross-risk vulnerability provides an answer.     

On the complexity of the continuous unbounded knapsack problem with uncertain coefficients

In this paper, a linear-time algorithm is developed for the minmax-regret version of the continuous unbounded knapsack problem with n items and uncertain objective function coefficients, where the interval estimates for these coefficients are known. This improves the previously known bound of time for this optimization problem.