基于风险厌恶的下游供应链转运问题研究

当需求面临较大不确定性并且供货周期很长的情况下,转运策略成为提高供应链效率的重要解决方案。本文以条件风险价值（Conditional Value—at—Risk,简称CVaR）为风险度量准则,定量地研究了集中决策下的两级供应链系统的转运问题。我们得出了下游批发商的最优订货决策主要依赖于需求分布、单位缺货成本和风险厌恶程度等因素的一般性结论,并得出了均衡最优订货组合所需要满足的条件,重点分析了当需求基于均匀分布时,单位缺货成本和风险厌恶程度对最优订货组合的影响。     

Control of Cash Reserves

The following paper deals with a special type of inventory control problem in which the commodity to be controlled is cash. An insurance company holds a reserve of cash, part of which is invested in short-term loans, the balance being held on current account in a bank. The company draws on the balance to meet the requirements of the company's stockbrokers, who invest money on its behalf, and to meet claims and expenses. If these drawings are large, an overdraft may result. Thus, as distinct from standard inventory problems, in this problem storage and penalty costs are well defined. The paper has two main features. Firstly, an approximate solution is found using characteristics of the optimal solution determined by dynamic programming. Secondly, an algorithm for long-duration processes of this type is derived.     

信息安全遵从行为的激励机制研究——惩罚的确定性与适度性

关于惩罚的确定性及其严重性是否能够有效地影响组织内部雇员的信息安全遵从行为,已有的研究结论尚存在着严重分歧。为了继续探索惩罚对信息安全遵从行为的影响作用,构建了信息安全遵从博弈模型,依据该模型和存在道德风险的委托人——代理人理论,分析了惩罚的确定性以及适度的惩罚严重性对信息安全遵从行为的激励机制,并对惩罚的适度性进行了数值模拟。研究表明:(1)作为委托人的组织可以设计出包含适度惩罚的最优激励契约,并获得最优的信息安全遵从收益;作为代理人的雇员不仅将接受该契约,并且会按照组织所期望的努力水平去遵从信息安全制度。(2)惩罚的确定性和适度性两者能够有效地影响雇员的信息安全遵从行为。(3)组织可以根据雇员的风险规避测度、外部机会收益、激励报酬以及信息安全产出结果这四个因素来设置适当的惩罚额度。这些研究结果将有助于信息安全管理者深入地理解并有效地管理组织内部雇员的信息安全遵从行为。     

不同补贴对象下闭环供应链信息共享价值研究

在一个制造商和一个零售商组成的二级闭环供应链中,为研究政府补贴下供应链需求信息共享对决策的影响及共享价值,针对两种补贴对象,构建并求解无信息共享和信息共享博弈模型,并进行仿真验证.研究表明:1)两种补贴对象下,制造商均能从信息共享中获益,零售商仅在绿色成本和回收成本较低时才会从信息共享中获益;绿色成本和回收成本稍高时,设计基于谈判势力的信息补偿机制能有效促进零售商共享信息.2)产品绿色度和回收率随预测需求量的提高而提高,批发价和零售价仅在回收成本较低时,才会随预测需求量的提高而提高.3)在仅补贴一方情况下,当补贴对象为低补贴一方时,两个主体所获的信息共享价值大;若对两者的补贴均较低,两个主体均希望补贴对象为零售商;若对两者的补贴均较高,零售商不愿共享需求信息.     

A note on issues of over-conservatism in robust optimization with cost uncertainty

We identify and discuss issues of hidden over-conservatism in robust linear optimization, when the uncertainty set is polyhedral with a budget of uncertainty constraint. The decision-maker selects the budget of uncertainty to reflect his degree of risk aversion, i.e. the maximum number of uncertain parameters that can take their worst-case value. In the first setting, the cost coefficients of the linear programming problem are uncertain, as is the case in portfolio management with random stock returns. We provide an example where, for moderate values of the budget, the optimal solution becomes independent of the nominal values of the parameters, i.e. is completely disconnected from its nominal counterpart, and discuss why this happens. The second setting focusses on linear optimization with uncertain upper bounds on the decision variables, which has applications in revenue management with uncertain demand and can be rewritten as a piecewise linear problem with cost uncertainty. We show in an example that it is possible to have more demand parameters equal their worst-case value than what is allowed by the budget of uncertainty, although the robust formulation is correct. We explain this apparent paradox.     

OPTIMAL HARVESTING OF FOREST AGE CLASSES UNDER PRICE UNCERTAINTY AND RISK AVERSION

ABSTRACT. . We analyze optimal forest harvesting under mean reverting and random walk timber price and include multiple age classes, forest owners' consumption‐savings decisions and risk aversion. This framework generalizes existing studies that assume a single stand and risk neutrality or include ad hoc risk aversion and obtain the result that uncertainty lengthens the optimal rotation. Including planting cost implies that price stochasticity may shorten the rotation period. Under the mean reverting price process, optimal harvesting becomes more sensitive to periodic price level, as compared to the random walk case. Including risk aversion completely changes the harvesting policy in the sense that, if the forest initially consists of just one age class, it is optimal to smooth the age class structure and have more frequent cuttings from younger age classes. With risk aversion, optimal cuttings depend on price level, even under a random walk price and zero replanting and harvesting costs. In addition, harvesting decisions become dependent on subjective time preference and forest owners' wealth.     

Stochastic dynamic nursing service budgeting

We address the nursing service budgeting problem from the department manager’s point of view. The model allocates the budget dynamically to three types of nursing care capacities: 1) permanent nurses, 2) temporary nurses, and 3) overtime. The quarterly tactical decisions are the aggregate weekly shift pattern of permanent nurses and the policy for hiring temporary nurses and using overtime. The decisions are optimized with respect to nursing care shortage and a soft-constraint on the annual budget. For the aggregate weekly shift pattern, permanent nurses require a notification lead-time of one quarter to prepare the personal rosters. Our model offers a solution to the nursing service budgeting problem that extends the existing literature by using a Markovian demand model, resolving the anticipation of the operational decisions, and applying general budget as well as shortage penalty functions.     

不完全信息和模糊厌恶下DC型养老金最优投资策略

在信息部分可观测的金融市场中,参与者可投资于一个无风险资产、一个滚动债券和一支股票。其中,股票的预期收益率由一个服从均值-回复过程的预测因子预测。参与者是模糊厌恶的,只能观测到股票价格和利率,却无法观测到预测因子。利用滤波技术和动态规划原理,得到了不完全信息和模糊厌恶下DC型养老金最优投资策略的解析式。进一步,利用敏感性分析和比较静态分析,对比仅考虑不完全信息、仅考虑模糊厌恶以及同时考虑不完全信息和模糊厌恶三种情形下的最优投资策略。结果表明同时考虑不完全信息和模糊厌恶时的最优投资策略最保守,仅考虑不完全信息时的最优投资策略对风险厌恶系数的变化最敏感。     

考虑零售商风险规避及努力因素的供应链协调与优化模型

引入零售商风险规避偏好,在努力水平影响需求的两种模式下,分别建立了销售回馈与惩罚契约模型。随后,探讨了单纯的销售回馈与惩罚契约能否实现供应链协调,以及协调时各契约参数满足的条件。最后,通过数值分析对契约的协调性进行进一步分析。     

Doubly uncertain transportation network: Degradable capacity and stochastic demand

This study developed a methodology to model doubly uncertain transportation network with stochastic link capacity degradation and stochastic demand. We consider that the total travel demand comprises of two parts, infrequent travelers and commuters. The traffic volume of infrequent travelers is stochastic, which adds to the network traffic in a random manner based on fixed route choice proportions. On the other hand, the traffic volume of commuters is stable or deterministic. Commuters acquire the network travel time variability from past experiences, factor them into their route choice considerations, and settle into a long-term habitual route choice equilibrium in which they have no incentive of switching away. To define this equilibrium, we introduce the notion of “travel time budget” to relate commuters’ risk aversion on route choices in the presence of travel time variability. The travel time budget varies among commuters according to their degrees of risk aversion and requirements on punctual arrivals. We then developed a mixed-equilibrium formulation to capture these stochastic considerations and illustrated its properties through some numerical studies.     

Uniform pricing and subsidy coordination mechanism in a two-tier healthcare system under a co-payment policy

Recently, the lengthy waiting time in public hospitals (called the public system) under the free healthcare policy has become a serious problem. To address this issue, motivated by the Japanese healthcare system, this paper investigates a two-tier co-payment healthcare system under a uniform pricing and subsidy coordination mechanism. In such a setting, the public system and the private system (i.e., the private hospitals) compete for market share with different objectives, whereas the government uniformly sets the service price and the subsidy rate to maximize social welfare under a total budget constraint. Compared with two free healthcare policy cases implemented in the Canadian and Australian healthcare systems respectively in terms of social welfare, the results show that when the market demand (or the patient service quality sensitivity) is sufficiently high (sufficiently low), the uniform pricing and subsidy coordination mechanism is better and worse otherwise; and when the patient's waiting sensitivity (or the total government budget) is in an appropriate middle range (sufficiently low or high), the mechanism can outperform than the free policy cases.     

激励机制和VaR约束下的DC养老金计划的最优投资

研究了DC养老金经理在单一管理费以及混合收费(同时收取管理费与绩效费)这两种不同的薪酬机制和损失厌恶下的最优投资组合问题。利用凹化方法得到了存在终端财富约束下的最优财富过程和最优投资策略的解析表达式。数值结果表明损失厌恶,VaR约束和薪酬机制会极大地影响最优终端财富的分布。特别地,在决策参照点较高时,损失厌恶会导致混合薪酬机制下最优终端财富的尾部风险较低。     

A distributed coordination mechanism for supply networks with asymmetric information

The paper analyses the problem of coordination in supply networks of multiple retailers and a single supplier, where partners have asymmetric, private information of demand and costs. After stating generic requirements like distributedness, truthfulness, efficiency and budget balance, we use the apparatus of mechanism design to devise a coordination mechanism that guarantees the above properties in the network. The resulting protocol is a novel realisation of the widely used Vendor Managed Inventory (VMI) where the responsibility of planning is at the supplier. We prove that together with the required generic properties a fair sharing of risks and benefits cannot be guaranteed. We illustrate the general mechanism with a detailed discussion of a specialised version, assuming that inventory planning is done according to the newsvendor model, and explore the operation of this protocol through computational experiments.     

交通拥堵管理中可交易电子券方案的公平性分析

利用损失厌恶理论中的参照依赖模型,构建用户的感知出行成本函数,在固定需求的交通网络中加入电子券交易费用率,建立均衡条件下的变分不等式模型。通过模拟仿真,说明市场交易费用率会影响电子券交易市场,政府可通过调节交易费用率提高电子券方案公平性。选取路网中所有起讫对间出行成本变化率波动的加权平均值,度量可交易电子券方案的公平性,综合考虑最小化系统出行总成本和最大化方案公平性两个目标,构造效用函数,分析不同权重下市场交易费用率对可交易电子券方案的影响,以期对电子券方案的公平性进行优化。     

碳交易驱动下建筑业主最优碳减排决策研究

对碳排放总量和强度都持续刚性增长的建筑领域,利用市场机制,借助碳交易来控制和减少其碳排放是一项重大的制度创新。本文通过构建多目标决策优化模型,探讨建筑业主在碳交易驱动形成的复杂动态环境下的最优碳减排策略;并基于实证数据进行情景耕耘,模拟和预测业主减排策略的动态适应性调整。研究发现:①业主碳减排决策受政府补贴强度和违规惩罚倍率调整的冲击更为显著;②目前碳市场“一刀切”的惩罚倍率极易使建筑业主陷入“明罚实奖”的惩罚悖论;③政府应采用“补贴退坡”政策并对不同类型的建筑业主进行精准补贴。     

政府对科技保险的最优财政补贴规模研究

运用机制设计理论建立信息激励模型,在完全信息、不完全信息、不完全信息加入可调整项三种情形下,对科技保险进行险种划分,得到在不同信息激励影响下的政府对保险公司的最优补贴规模.运用期望收益理论,针对科技研发成功或不成功、科技企业投保或不投保的情形,建立政府补贴投保企业的最优补贴规模模型,得出政府对投保企业补贴规模的限制范围.     

具有惩罚因子的模糊集约生产计划

研究基于模糊环境下的集约生产计划问题,并设计了带有惩罚因子的模糊优化模型,以实现生产费用和惩罚费用之和最小.通过模糊变量和模糊等式定义的描述,简化了模型,并给出机会约束规划方法进行模型求解的整体步骤.通过仿真结果和灵敏度分析,表明模型和方法的有效性,并为决策者在模糊环境下的决策提供支持.     

基于不同政府补贴策略的供应链绿色努力决策比较研究

研究由单一制造商与单一零售商组成的二级绿色供应链,探讨在同时考虑制造商与零售商绿色努力情况下政府补贴策略对供应链绿色努力与定价决策的影响,比较分析无补贴策略、制造商补贴策略与消费者补贴策略对决策影响的差异性,并进一步考虑零售商的风险规避特征对最优决策的影响。结果表明,政府补贴能够激励制造商与零售商的绿色努力行为,对供应链的绿色发展总是有利的;且制造商补贴策略下的绿色质量水平高于消费者补贴策略,但对供应链利润而言并不是最优的;而在消费者补贴策略下,尽管产品的绿色质量水平不是最优的,但供应链可以获得最高的利润。研究还发现,风险规避特征不会改变参数对最优决策与最优利润的影响趋势,但会降低零售商的绿色努力积极性,导致其利润的下降。     

A Markov decision problem in a risk model with interest rate and Markovian environment

We consider the compound binomial model in a Markovian environment presented by Cossette et al.(2004). We modify the model via assuming that the company receives interest on the surplus and a positive real-valued premium per unit time, and introducing a control strategy of periodic dividend payments. A Markov decision problem arises and the control objective is to maximize the cumulative expected discounted dividends paid to the shareholders until ruin minus a discounted penalty for ruin. We show that under the absence of a ceiling of dividend rates the optimal strategy is a conditional band strategy given the current state of the environment process. Under the presence of a ceiling for dividend rates, the character of the optimal control strategy is given. In addition, we offer an algorithm for the optimal strategy and the optimal value function.Numerical results are provided to illustrate the algorithm and the impact of the penalty.     

Analysis of Current Penalty Schemes for Violations of Antitrust Laws

The main feature of the penalty schemes described in current sentencing guidelines is that the fine is based on the accumulated gains from cartel activities or price-fixing activities for the firm. The regulations suggest modeling the penalty as an increasing function of the accumulated illegal gains from price fixing to the firm, so that the history of the violation is taken into account. We incorporate these features of the penalty scheme into an optimal control model of a profit-maximizing firm under antitrust enforcement. To determine the effect of taking into account the history of the violation, we compare the outcome of this model with a model where the penalty is fixed. The analysis of the latter model implies that complete deterrence can be achieved only at the cost of shutting down the firm. The proportional scheme improves upon the fixed penalty, since it can ensure complete deterrence in the long run, even when penalties are moderate. Phase-diagram analysis shows that, the higher the probability and severity of punishment, the sooner cartel formation is blocked. Further, a sensitivity analysis is provided to show which strategies are most successful in reducing the degree of price fixing. It turns out that, when the penalties are already high, the antitrust policy aiming at a further increase in the severity of punishment is less efficient than the policy that increases the probability of punishment. The authors thank Eric van Damme, Thomas Fent, and an anonymous referee for stimulating discussions and valuable comments.