Maximum principle for partially-observed optimal control problems of stochastic delay systems

This paper is concerned with partially-observed optimal control problems for stochastic delay systems. Combining Girsanov’s theorem with a standard variational technique, the authors obtain a maximum principle on the assumption that the system equation contains time delay and the control domain is convex. The related adjoint processes are characterized as solutions to anticipated backward stochastic differential equations in finite-dimensional spaces. Then, the proposed theoretical result is applied to study partially-observed linear-quadratic optimal control problem for stochastic delay system and an explicit observable control variable is given.     

Stochastic maximum principle for optimal control problems of forward-backward delay systems involving impulse controls

This paper is concerned with the optimal control problems of forward-backward delay systems involving impulse controls. The authors establish a stochastic maximum principle for this kind of systems. The most distinguishing features of the proposed problem are that the control variables consist of regular and impulsive controls, both with time delay, and that the domain of regular control is not necessarily convex. The authors obtain the necessary and sufficient conditions for optimal controls, which have potential applications in mathematical finance.     

A DYNAMIC OPTIMAL ADVERTISING MODEL FOR NEW PRODUCTS

Many dynamic optimal control models for advertising make efforts to solve the problem of determining optimal advertising expenditures and other variables of interest over time for a firm or several competing firms,However,after analyzing the extant literature,one can find that few dynamic optimal advertising models available consider the problem within the product diffusion framework.Furthermore,the established models involving product diffusion are inspired by the Bass model,which has been out of date.This paper poses a dynamic optimal advertising model for new products,which considers the product diffusion based on the relative newly developed generalized version of the Bass model.In this paper,the optimal control model is used to derive the optimal advertising expenditure policy,which gives some implications to advertising practice.     

随机需求下单制造商两零售商合作广告协调模型

考虑了由单个制造商两个零售商所组成的供应链生产销售Newsvendor型产品的合作广告问题.分析了制造商的品牌广告投入及两个竞争零售商的地方促销广告投入对每个零售商需求的影响,分别给出了分散决策和一体化决策下制造商的最优广告投入,两个竞争零售商的最优地方促销广告投入及销售期初的最优订购批量,利用利润共享契约使得供应链达到协调,并从供应链各成员风险偏好的角度对渠道收益的分配问题进行了探讨.     

Stochastic maximum principle for mixed regular-singular control problems of forward-backward systems

This paper considers a stochastic optimal control problem of a forward-backward system with regular-singular controls where the set of regular controls is not necessarily convex and the regular control enters the diffusion coefficient. This control problem is difficult to solve with the classical method of spike variation. The authors use the approach of relaxed controls to establish maximum principle for this stochastic optimal control problem. Sufficient optimality conditions are also investigated.     

Optimal Insurance-Package and Investment Problem for an Insurer

An insurance-package is a combination being tie-in at least two different categories of insurances with different underwriting-yield-rate. In this paper, the optimal insurance-package and investment problem is investigated by maximizing the insurer's exponential utility of terminal wealth to find the optimal combination-share and investment strategy. Using the methods of stochastic analysis and stochastic optimal control, the Hamilton-Jacobi-Bellman(HJB) equations are established, the optimal strategy and the value function are obtained in closed form. By comparing with classical results, it shows that the insurance-package can enhance the utility of terminal wealth, meanwhile,reduce the insurer's claim risk.     

Stabilization of Continuous-Time Systems Against Stochastic Network Uncertainties: Fundamental Variance Bounds

This paper studies the stabilizability and stabilization of continuous-time systems in the presence of stochastic multiplicative uncertainties. The authors consider multi-input, multi-output(MIMO) linear time-invariant systems subject to multiple static, structured stochastic uncertainties,and seek to derive fundamental conditions to ensure that a system can be stabilized under a mean-square criterion. In the stochastic control framework, this problem can be considered as one of optimal control under state-or input-dependent random noises, while in the networked control setting, a problem of networked feedback stabilization over lossy communication channels. The authors adopt a mean-square small gain analysis approach, and obtain necessary and sufficient conditions for a system to be meansquare stabilizable via output feedback. For single-input, single-output(SISO) systems, the condition provides an analytical bound, demonstrating explicitly how plant unstable poles, nonminimum phase zeros, and time delay may impose a limit on the uncertainty variance required for mean-square stabilization. For MIMO minimum phase systems with possible delays, the condition amounts to solving a generalized eigenvalue problem, readily solvable using linear matrix inequality optimization techniques.     

Decentralized Control of Discrete-Time System with Delay in Mean Field LQR Problem

This paper studies the decentralized optimal control of discrete-time system with input delay,where a large number of agents with the identical decoupling dynamical equations and the coupling cost function through the mean field are considered.The decentralized and centralized optimal controllers are proposed by the optimal tracking control of LQR problem with delay.They are proved that the optimal controllers and the optimal cost function of the centralized and decentralized solutions are equivalent for the optimal control problem.An illustrative example is given to show the efficiency of the decentralized optimal controllers.     

OPTIMAL CONTROL OF A CLASS OF DISTRIBUTED PARAMETER DELAY SYSTEMS

1.IntroductionManyphysicalsystems,suchajsthemodynamics,electrodynamics,populationbiology,aregovernedbydifferentialequations,integrodifferentialequationsormoregenerallyfunctionaldifferentialevolutionequationsonBanachspace.Associatedoptimalcontrolprobl...     

The maximum principle for partially observed optimal control of forward-backward stochastic systems with random jumps

This paper studies the problem of partially observed optimal control for forward-backward stochastic systems which are driven both by Brownian motions and an independent Poisson random measure. Combining forward-backward stochastic differential equation theory with certain classical convex variational techniques, the necessary maximum principle is proved for the partially observed optimal control, where the control domain is a nonempty convex set. Under certain convexity assumptions, the author also gives the sufficient conditions of an optimal control for the aforementioned optimal optimal problem. To illustrate the theoretical result, the author also works out an example of partial information linear-quadratic optimal control, and finds an explicit expression of the corresponding optimal control by applying the necessary and sufficient maximum principle.     

Worst-Case Investment Strategy with Delay

This paper considers a worst-case investment optimization problem with delay for a fund manager who is in a crash-threatened financial market. Driven by existing of capital inflow/outflow related to history performance, we investigate the optimal investment strategies under the worst-case scenario and the stochastic control framework with delay. The financial market is assumed to be either in a normal state(crash-free) or in a crash state. In the normal state the prices of risky assets behave as geometric Brownian motion, and in the crash state the prices of risky assets suddenly drop by a certain relative amount, which induces to a dropping of the total wealth relative to that of crash-free state. We obtain the ordinary differential equations satisfied by the optimal investment strategies and the optimal value functions under the power and exponential utilities, respectively. Finally, a numerical simulation is provided to illustrate the sensitivity of the optimal strategies with respective to the model parameters.     

供应链中耐用品的广告投入和零售价策略分析

针对供应链中制造商和零售商关于耐用商品的合作广告和零售价定价问题,本文构建了一个微分博弈模型. 将市场累计销售量作为状态变量,并把广告和价格因素引入到市场累计销售量的动态方程中. 运用汉密尔顿-雅可比-贝尔曼方程,分别得到了零售商的最优定价和广告投入策略以及制造商对零售商广告成本的最优分担比例;发现零售商的最优定价和制造商的分担比例均为常数,而零售商的广告投入随市场累计销售量的增加而递减;并且给出了制造商对零售商进行广告补贴的阈值. 最后,给出了各厂商决策变量的比较静态分析.     

Coordinating Pricing,Ordering and Advertising for Perishable Products Over an Infinite Horizon

Numerous empirical studies show that advertising effort can stimulate demand in both current and future periods, and there is an interaction between pricing, advertising and ordering decisions. How do these decisions interact with each other and what is the effect of advertising on pricing and ordering decisions? To understand this interaction, we consider a newsvendor-type firm that sells a perishable product in a stable market and dynamically determines the joint ordering, pricing and advertising strategies. The problem is modeled as an infinite horizon newsvendor problem with an advertising carryover effect and price-sensitive demand. We characterize the optimal pricing, advertising and inventory strategies and their comparative statics, and consider how this policy differs from the traditional approach without the advertising effect. We show that the optimal effective advertising level is monotonically increasing with the effective advertising level in the previous period, and hence the optimal strategies (advertising, pricing, inventory level) globally converge to the steady states in the long run. We numerically show that the optimal policy can reap significant profit, which underscores the importance of the advertising-driven ordering and pricing strategies.     

Maximum Principle for Non-Zero Sum Stochastic Differential Game with Discrete and Distributed Delays

This technical note is concerned with the maximum principle for a non-zero sum stochastic differential game with discrete and distributed delays. Not only the state variable, but also control variables of players involve discrete and distributed delays. By virtue of the duality method and the generalized anticipated backward stochastic differential equations, the author establishes a necessary maximum principle and a sufficient verification theorem. To explain theoretical results, the author applies them to a dynamic advertising game problem.     

A Mean-Field Optimal Control for Fully Coupled Forward-Backward Stochastic Control Systems with Lévy Processes

This paper is concerned with a class of mean-field type stochastic optimal control systems, which are governed by fully coupled mean-field forward-backward stochastic differential equations with Teugels martingales associated to Lévy processes. In these systems, the coefficients contain not only the state processes but also their marginal distribution, and the cost function is of mean-field type as well. The necessary and sufficient conditions for such optimal problems are obtained. Furthermore, the applications to the linear quadratic stochastic optimization control problem are investigated.

     

带有两种营销模式的供应链合作广告协调模型

本文考虑了带有直营店和代理商两种营销模式的Newsvendor型产品合作广告问题,分别建立了分散决策和集中控制下制造商和代理商的最优广告决策模型,分析了需求的随机性及直营店的营销模式对供应链双方广告决策的影响．给出了一个基于地方促销广告费用分摊的策略以实现供应链协调．最后,用数值仿真验证了本文的相关结论并得到一些重要的管理启示．     

MAXIMUM PRINCIPLE FOR OPTIMAL CONTROLPROBLEM OF FULLY COUPLEDFORWARD-BACKWARD STOCHASTIC SYSTEMS

1.IntroductionLet(fi,F,P)beaprobabilityspaceand{Bt}tZobead-dimensionalBrownianmotioninthisspace.Let{R}tZobethenaturalfiltrationofthisBrownianmotion.Weconsiderthefollowingfullycoupledforward-backwardstochasticsystems:where(x,y,z)takesvaluesinR"xacxRTnxd.LetUbeanonemptyconvexsubsetofR',Anelementofadiscalledanadmissiblecontrol.Wecandefinethefollowingcostfunction:TheoptimalcontrolproblemistominimizethecostfunctionJ(v(.))overadmissiblecontrols.Anadmissiblecontrolu(.)iscalledanoptimalcontrol…     

FORWARD-BACKWARD STOCHASTIC DIFFERENTIAL EQUATIONS, LINEAR QUADRATIC STOCHASTIC OPTIMAL CONTROL AND NONZERO SUM DIFFERENTIAL GAMES

In this paper, we use the solutions of forward-backward stochastic differential equations to get the explicit form of the optimal control for linear quadratic stochastic optimal control problem and the open-loop Nash equilibrium point for nonzero sum differential games problem. We also discuss the solvability of the generalized Riccati equation system and give the linear feedback regulator for the optimal control problem using the solution of this kind of Riccati equation system.     

Mean-square exponential stability for stochastic time-varying delay systems with Markovian jumping parameters: a delay decomposition approach

The mean-square exponential stability problem is investigated for a class of stochastic time-varying delay systems with Markovian jumping parameters.By decomposing the delay interval into multiple equidistant subintervals,a new delay-dependent and decay-rate-dependent criterion is presented based on constructing a novel Lyapunov functional and employing stochastic analysis technique.Besides,the decay rate has no conventional constraint and can be selected according to different practical conditions.Finally,two numerical examples are provided to show that the obtained result has less conservatism than some existing ones in the literature.     

广告竞争模型的最优控制策略研究

考虑了竞争性和信息性两种广告对企业市场份额不同作用,提出一个在两强竞争情况下的动态广告投入模型,运用动态规划的Bellman方程求出模型的闭环Nash均衡解,得到企业应采取的广告最优控制策略,并进一步研究Nash均衡解有经济意义的参数范围以及Nash均衡解收敛的条件.最后用一个数值例子分析了Nash均衡下的广告策略.