基于Hurwicz准则的不确定养老金最优投资策略问题

本文提出一种新的养老金最优投资策略模型,研究了带有不确定工资过程的DC型养老金最优投资策略问题.以二次损失函数的Hurwicz加权平均值最小化为目标,针对两类相对财富过程,给出了养老金最优投资策略的显式表达式.最后,通过数值分析,研究了模型参数对最优投资策略的影响.     

生态平衡制约下离散尺度结构种群的最优收获

研究基于扩展Leslie投影矩阵的离散尺度结构种群模型的最优收获问题,约束条件包括生态平衡和开发成本等.运用凸优化理论证明了最优收获策略的存在性,导出了最优收获模式,应用模型参数给出了收获比率.结论显示:最优策略具有两阶段结构.     

复合二项对偶模型的最优分红问题

研究复合二项对偶模型的最优分红问题,通过分析HJB方程得到了最优分红策略和相应的最优值函数之间的关系以及最优值函数的简单计算方法.通过讨论最优红利策略的一些性质得到了最优值函数的可无限逼近的上界和下界.     

跳-扩散风险模型的最优投资和再保险策略

本文对跳-扩散风险模型,在赔付进行比例再保险,以及盈余投资于无风险资产和风险资产的条件下,研究使得最终财富的指数期望效用最大的最优投资和比例再保险策略.得到最优投资策略和最优再保险策略,以及最大指数期望效用函数的显式表达式,发现最优策略和值函数都受到无风险利率的影响.最后通过数值计算,得到最优投资和比例再保险策略,以及值函数与模型各个参数之间的关系.     

考虑Vasicek利率和相依风险的最优投资与再保险

本文研究了利率由Vasicek过程描述,两类保险业务具有相依风险的最优投资和再保险模型.盈余过程由扩散近似模型刻画,保险人的目标是在给定期望终端财富的情况下,寻找使得终端财富的方差最小的投资和再保险策略.通过使用随机线性二次最优控制理论,建立Hamilton-Jacobi-Bellman(HJB)方程,我们获得了值函数的精确表达式以及最优投资和再保险策略.另外,我们给出了有效策略和有效前沿.最后,通过数值例子说明了模型参数对最优投资和再保险策略的影响.     

部分信息情形下利率非零时的最优消费投资模型研究

考虑了部分信息情形下市场利率非零时的最优消费投资模型,讨论了相应的最优消费投资策略.最后探讨了当扩散系数可逆且漂移系数服从已知分布时的贝叶斯特例,给出了最优交易策略的明确表达式.     

带利率和随机观测时间的布朗运动模型中最优分红策略

本文研究了带利率和随机观测时间的布朗运动模型中的最优分红问题.利用随机控制理论,获得了最优值函数相应的HJB方程,表明最优分红策略是障碍策略,并给出了最优值函数的显式表达式,推广了文献[19]的结果.     

快速补货模式下的动态定价与库存联合策略

在供应有限的情况下,研究常规补货和快速补货下商品动态定价问题.首先,建立了动态规划模型,理论证明了最优库存策略是基于(s,S)策略下改进的基本库存策略.其次,提出了一种启发式策略求复杂系统的最优策略,启发式算法能够求出最优价格和最优库存水平.最后,数值算例研究表明,库存管理中采用快速补货提高了零售商的利润;初始库存水平越高零售商的利润越高.     

柔性生产下马氏需求EPQ模型的最优(P,Q,T)策略

随机需求环境下研究柔性制造系统的经济生产批量(Economic Production Quantity,EPQ)模型的最优生产策略问题.在假设需求满足马尔可夫性且为需求状态依赖的条件下,根据顾客的需求程度对市场需求进行状态划分,建立了马氏需求模型,对系统未来的需求提出了科学的预测方法.在该模型的基础上,结合柔性制造系统的理论,构建了柔性生产下马氏需求EPQ模型.利用函数的凸性研究了新的EPQ模型的最优解的存在性,进而提出模型的最优(P,Q,T)策略.模型的数值算例表明,利用最优(P,Q,T)策略可以提高制造系统的生产率、缩短产品生产周期及实现小批量的生产模式.     

最优比例与超额损失组合再保险下的破产概率

本文站在保险人的立场上,讨论了保险公司的最优组合再保险问题.通过纯粹比例再保险,纯粹超额损失再保险,或者这两类再保险的组合方式,把保险公司的部分风险分担出去.在最大化调节系数的最优准则下,我们得出了布朗运动模型和复合Poisson模型中最优值的显示表达,并且给出了复合Poisson模型中最优策略下破产概率的最小指数上界.我们还得出结论:在一定的条件下,总存在一种纯粹超额损失再保险策略比任何一类组合再保险策略都要好.最后,通过一些数例和图表来进一步说明我们在文中所获得的结论.     

A Gradient Flow Approach to Optimal Model Reduction of Discrete-Time Periodic Systems

This paper is concerned with the optimal model reduction for linear discrete periodic time-varying systems and digital filters. Specifically, for a given stable periodic time-varying model, we shall seek a lower order periodic time-varying model to approximate the original model in an optimal H ₂ norm sense. By orthogonal projections of the original model, we convert the optimal periodic model reduction problem into an unconstrained optimization problem. Two effective algorithms are then developed to solve the optimization problem. The algorithms ensure that the H ₂ cost decreases monotonically and converges to an optimal (local) solution. Numerical examples are given to demonstrate the computational efficiency of the proposed method. The present paper extends the optimal model reduction for linear time invariant systems to linear periodic discrete time-varying systems.     

Optimal excess-of-loss reinsurance and investment problem for an insurer with jump–diffusion risk process under the Heston model

In this paper, we study the optimal excess-of-loss reinsurance and investment problem for an insurer with jump–diffusion risk model. The insurer is allowed to purchase reinsurance and invest in one risk-free asset and one risky asset whose price process satisfies the Heston model. The objective of the insurer is to maximize the expected exponential utility of terminal wealth. By applying stochastic optimal control approach, we obtain the optimal strategy and value function explicitly. In addition, a verification theorem is provided and the properties of the optimal strategy are discussed. Finally, we present a numerical example to illustrate the effects of model parameters on the optimal investment–reinsurance strategy and the optimal value function.     

A bilevel fuzzy principal-agent model for optimal nonlinear taxation problems

This paper presents a bilevel fuzzy principal-agent model for optimal nonlinear taxation problems with asymmetric information, in which the government and the monopolist are the principals, the consumer is their agent. Since the assessment of the government and the monopolist about the consumer’s taste is subjective, therefore, it is reasonable to characterize this assessment as a fuzzy variable. What’s more, a bilevel fuzzy optimal nonlinear taxation model is developed with the purpose of maximizing the expected social welfare and the monopolist’s expected welfare under the incentive feasible mechanism. The equivalent model for the bilevel fuzzy optimal nonlinear taxation model is presented and Pontryagin maximum principle is adopted to obtain the necessary conditions of the solutions for the fuzzy optimal nonlinear taxation problems. Finally, one numerical example is given to illustrate the effectiveness of the proposed model, the results demonstrate that the consumer’s purchased quantity not only relates with the consumer’s taste, but also depends on the structure of the social welfare.     

Modeling framework for optimal evacuation of large-scale crowded pedestrian facilities

The paper presents a simulation–optimization modeling framework for the evacuation of large-scale pedestrian facilities with multiple exit gates. The framework integrates a genetic algorithm (GA) and a microscopic pedestrian simulation–assignment model. The GA searches for the optimal evacuation plan, while the simulation model guides the search through evaluating the quality of the generated evacuation plans. Evacuees are assumed to receive evacuation instructions in terms of the optimal exit gates and evacuation start times. The framework is applied to develop an optimal evacuation plan for a hypothetical crowded exhibition hall. The obtained results show that the model converges to a superior optimal evacuation plan within an acceptable number of iterations. In addition, the obtained evacuation plan outperforms conventional plans that implement nearest-gate immediate evacuation strategies.     

Lower bounding aggregation and direct computation for an infinite horizon one-reservoir model

We present a specialized policy iteration method for the computation of optimal and approximately optimal policies for a discrete-time model of a single reservoir whose discharges generate hydroelectric power. The model is described in (Lamond et al., 1995) and (Drouin et al., 1996), where the special structure of optimal policies is given and an approximate value iteration method is presented, using piecewise affine approximations of the optimal return functions. Here, we present a finite method for computing an optimal policy in O(n³) arithmetic operations, where n is the number of states in the associated Markov decision process, and a finite method for computing a lower bound on the optimal value function in O(m²n) where m is the number of nodes of the piecewise affine approximation.     

Optimal lot size and inspection policy for products sold with warranty

This paper develops a mathematical model to jointly determine the optimal lot size and product inspection policy for a deteriorating production system, when products are sold with free minimal repair warranty. Due to system deterioration, a last-K product inspection scheme is proposed, under which the last K products in a production lot are inspected and nonconforming products found are reworked. Based on the model, we show that there exist a unique optimal lot size and a corresponding inspection policy such that the expected total cost per unit time is minimized. Since there is no closed-form expression for the optimal lot size, an upper bound and approximate solutions are obtained to facilitate the search process. Furthermore, an algorithm is provided to efficiently search for the optimal policy and the performance of the optimal policy is evaluated through numerical examples.     

Calculating risk neutral probabilities and optimal portfolio policies in a dynamic investment model with downside risk control

This paper presents a method for solving multiperiod investment models with downside risk control characterized by the portfolio’s worst outcome. The stochastic programming problem is decomposed into two subproblems: a nonlinear optimization model identifying the optimal terminal wealth distribution and a stochastic linear programming model replicating the identified optimal portfolio wealth. The replicating portfolio coincides with the optimal solution to the investor’s problem if the market is frictionless. The multiperiod stochastic linear programming model tests for the absence of arbitrage opportunities and its dual feasible solutions generate all risk neutral probability measures. When there are constraints such as liquidity or position requirements, the method yields approximate portfolio policies by minimizing the initial cost of the replication portfolio. A numerical example illustrates the difference between the replicating result and the optimal unconstrained portfolio.     

Optimal intervention policies for a multidimensional simple epidemic process

We consider a deterministic simple epidemic process in which the susceptibles are exposed to n+1 diseases. It is assumed that one disease is relatively harmless while the others cause serious symptoms. Policies for introducing infection by the harmless disease are considered and, under a suitable cost structure, the optimal policy that minimises the future cost for every initial state is found. For the corresponding stochastic model, the optimal policy is found by implementing a suitable dynamic programming algorithm, and is compared numerically with the optimal policy for the deterministic model.     

Inventory control as a discrete system control for the fixed-order quantity system

This paper shows how to model a problem to find optimal number of replenishments in the fixed-order quantity system as a basic problem of optimal control of the discrete system. The decision environment is deterministic and the time horizon is finite. A discrete system consists of the law of dynamics, control domain and performance criterion. It is primarily a simulation model of the inventory dynamics, but the performance criterion enables various order strategies to be compared. The dynamics of state variables depends on the inflow and outflow rates. This paper explicitly defines flow regulators for the four patterns of the inventory: discrete inflow – continuous/discrete outflow and continuous inflow – continuous/discrete outflow. It has been discussed how to use suggested model for variants of the fixed-order quantity system as the scenarios of the model. To find the optimal process, the simulation-based optimization is used.     

Multistage multiproduct advertising budgeting

We propose and analyze an effective model for the Multistage Multiproduct Advertising Budgeting problem. This model optimizes the advertising investment for several products, by considering cross elasticities, different sales drivers and the whole planning horizon. We derive a simple procedure to compute the optimal advertising budget and its optimal allocation. The model was tested to plan a realistic advertising campaign. We observed that the multistage approach may significantly increase the advertising profit, compared to the successive application of the single stage approach.