Turnpike properties for a class of piecewise deterministic systems arising in manufacturing flow control

This paper deals with a general class of piecewise deterministic control systems that encompasses FMS flow control models. One uses the Markov renewal decision process formalism to characterize optimal policies via a discrete event dynamic programming approach. A family of control problems with a random stopping time is associated with these optimality conditions. These problems can be reformulated as infinite horizon deterministic control problems. It is then shown how the so-calledturnpike property should hold for these deterministic control problems under classical convexity assumptions. These turnpikes have the same generic properties as the attractors obtained via a problem specific approach in FMS flow control models and production planning and are calledhedging points in this literature.This research has been supported by NSERC-Canada, Grants No. A4952 by FCAR-Québec, Grant No. 88EQ3528, Actions Structurantes, MESS-Québec, Grant No. 6.1/7.4(28), and FNRS-Switzerland.     

Solution of a class of stochastic linear-convex control problems using deterministic equivalents

In this paper, we identify a new class of stochastic linearconvex optimal control problems, whose solution can be obtained by solving appropriate equivalent deterministic optimal control problems. The term linear-convex is meant to imply that the dynamics is linear and the cost function is convex in the state variables, linear in the control variables, and separable. Moreover, some of the coefficients in the dynamics are allowed to be random and the expectations of the control variables are allowed to be constrained. For any stochastic linear-convex problem, the equivalent deterministic problem is obtained. Furthermore, it is shown that the optimal feedback policy of the stochastic problem is affine in its current state, where the affine transformation depends explicitly on the optimal solution of the equivalent deterministic problem in a simple way. The result is illustrated by its application to a simple stochastic inventory control problem.This research was supported in part by NSERC Grant A4617, by SSHRC Grant 410-83-0888, and by an INRIA Post-Doctoral Fellowship.     

Deterministic equivalent for a continuous-time linear-convex stochastic control problem

We consider a finite-horizon control model with additive input. There are two convex functions which describe the running cost and the terminal cost within the system. The cost of input is proportional to the input and can take both positive and negative values. It is shown that there exists a deterministic control problem whose optimal cost is the same as the one in the stochastic control problem. The optimal policy for the stochastic problem consists of keeping the process as close to the optimal deterministic trajectory as possible.This research is supported by NSERC Grant A4619, MRCO, NSF Grant DMS-86-01510, and AFOSR Grant 87-0278.     

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??This paper extends a class of discount problem of singular
stochastic control with stopping time. We extend the state process and cost function
to general case. By stochastic analysis and optimal control theory, the "fail-stop"
control strategy is its optimal control. The conditions of the "fail-stop" strategy
and optimal control function and control method are given. The conclusion in this
paper has a fairly deep application.     

随机递归最优控制和混合最优控制问题

对随机递归最优控制问题即代价函数由特定倒向随机微分方程解来描述和递归混合最优控制问题即控制者还需 决定最优停止时刻, 得到了最优控制的存在性结果. 在一类等价概率测度集中,还给出了递归最优值函数的最小和最大数学期望.     

一类非对称的“跳-停”奇异型随机控制

研究了一类带停时的非对称的奇异型随机控制的折扣问题,不论是从受控状态过程还是从费用函数均推广为较一般的情形,得到"跳-停"策略是其最优控制策略,并给出了"跳-停"策略存在的条件、最优费用函数以及控制方法,所得的结论在实际中有较深的应用背景。     

Existence and global asymptotic stability of optimal trajectories for a class of infinite-horizon,nonconvex systems

Sufficient conditions for the existence of optimal trajectories and for the global asymptotic stability of these trajectories are given for a class of nonconvex and nonautonomous systems controlled over an infinite-time horizon. The concept ofG-supported trajectory is introduced. It is shown that, under some assumptions, aG-supported trajectory is overtaking and is globally asymptotically stable. The concept of overtaking trajectory has been previously defined as a notion of optimality on an infinite-time domain. For autonomous systems, under weaker conditions, one guarantees the existence of weakly overtaking trajectories. Finally, it is shown howG-supported trajectories can be obtained, and an application to the study of a pre-predator ecosystem optimally harvested is sketched.This research has been partially supported by the Canada Council, Grant No. S.741122X2, and by the Programme FCAC de la DGES, Ministère de l'Education du Québec, Québec, Canada.     

Lower semicontinuity property of multiparameter optimal stopping value and its application to multiparameter prophet inequalities

This paper is concerned with the optimal stopping problem for discrete time multiparameter stochastic processes with the index set Nd. The optimal stopping value of a discrete time multiparameter integrable stochastic process whose negative part is uniformly integrable, is lower semicontinuous for the topology of convergence in distribution. The multiparameter version of prophet inequality for the one-parameter optimal stopping problem is formulated and the lower semicontinuity property of the optimal stopping value is applied to the multiparameter prophet inequality.     

有限时区上的最优转换和停止问题

讨论了有限时区上的最优转换和停止问题,它是一类同时具备脉冲控制和最优停止特征的最优控制问题.问题的最优值以及最优转换和停止决策可以由具有混合障碍的多维反射倒向随机微分方程的解来刻画.接着考虑了形式更一般的反射倒向随机微分方程并证明了方程解的存在唯一性.     

一类具漂移的“跳-停”奇异型随机控制

以随机分析和最优控制理论为基础,讨论了一类带停时的奇异型随机控制问题.在原模型状态过程的基础上添加了漂移因子,并将原模型中的控制费用函数推广为一般的费用函数.在某些条件下,得到"跳一停"策略是其最优控制策略,并给出了"跳一停"策略存在的条件以及控制方法,所得的结论在实际中有较深的应用背景.     

有限时区上的最优转换和停止问题

讨论了有限时区上的最优转换和停止问题,它是一类同时具备脉冲控制和最优停止特征的最优控制问题.问题的最优值以及最优转换和停止决策可以由具有混合障碍的多维反射倒向随机微分方程的解来刻画.接着考虑了形式更一般的反射倒向随机微分方程并证明了方程解的存在唯一性.     

Equivalent models for finite-fuel stochastic control

A stochastic control problem with finite-fuel constraint, of the type studied by Bene?, Shepp and Witsenhausen (1980), is solved explicitly. It is shown to be reducible to “simpler” stochastic optimization problems, such as optimal stopping and singular control for Brownian motion with unlimited fuel.     

Continuity Properties of Optimal Multiple Stopping Value

This article is concerned with the optimal multiple stopping problem for discrete time finite stage stochastic processes. We study lower semicontinuity and continuity properties of optimal stopping values with respect to the topology of convergence in distribution. Also, we formulate the multiple stopping version of the prophet inequality for the optimal stopping problem and apply the lower semicontinuity property of optimal stopping values to the prophet inequality for the optimal multiple stopping problem.     

A maximum principle for optimal control problem of fully coupled forward-backward stochastic systems with partial information

The paper is concerned with a stochastic optimal control problem in which the controlled system is described by a fully coupled nonlinear forward-backward stochastic differential equation driven by a Brownian motion. It is required that all admissible control processes are adapted to a given subfiltration of the filtration generated by the underlying Brownian motion. For this type of partial information control, one sufficient (a verification theorem) and one necessary conditions of optimality are proved. The control domain need to be convex and the forward diffusion coefficient of the system can contain the control variable. This work was partially supported by Basic Research Program of China (Grant No. 2007CB814904), National Natural Science Foundation of China (Grant No. 10325101) and Natural Science Foundation of Zhejiang Province (Grant No. Y605478, Y606667)     

Switching control of piecewise-deterministic processes

A finite collection of piecewise-deterministic processes are controlled in order to minimize the expected value of a performance functional with continuous operating cost and discrete switching control costs. The solution of the associated dynamic programming equation is obtained by an iterative approximation using optimal stopping time problems.This research was supported in part by NSF Grant No. DMS-8508651 and by University of Tennessee Science Alliance Research Incentive Award.     

Consumption-Investment Problem with Subsistence Consumption,Bankruptcy, and Random Market Coefficients

We consider a general continuous-time finite-horizon single-agent consumption and portfolio decision problem with subsistence consumption and value of bankruptcy. Our analysis allows for random market coefficients and general continuously differentiable concave utility functions. We study the time of bankruptcy as a problem of optimal stopping, and succeed in obtaining explicit formulas for the optimal consumption and wealth processes in terms of the optimal bankruptcy time. This paper extends the results of Karatzas, Lehoczky, and Shreve (Ref. 1) on the maximization of expected utility from consumption in a financial market with random coefficients by incorporating subsistence consumption and bankruptcy. It also addresses the random coefficients and finite-horizon version of the problem treated by Sethi, Taksar, and Presman (Ref. 2). The mathematical tools used in our analysis are optimal stopping, stochastic control, martingale theory, and Girsanov change of measure.     

Sur un problème de dynkin

Résumé Cet article a bénéficié de nombreuses conversations avec G. Mokobodzki. Qu'il en soit ici remercié.

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The purpose of this paper is to apply methods previously developed by the author for the optimal stopping problem to a zero sum game where both control variables are stopping times.

     

Stochastic bargaining models

Two stochastic models of labor-management negotiations are proposed and solved explicity. The cost function considered is such that either a penalty is incurred as long as negotiations take place, or an infinite penalty is incurred if a settlement is not reached before a fixed time. Furthermore, the cost function takes the risk sensitivity of the optimizers into account.This research was supported by the Natural Sciences and Engineering Research Council of Canada and by the fund FCAR of Québec.     

A Connection between Singular Stochastic Control and Optimal Stopping

We show that the value function of a singular stochastic control problem is equal to the integral of the value function of an associated optimal stopping problem. The connection is proved for a general class of diffusions using the method of viscosity solutions.     

A Connection between Singular Stochastic Control and Optimal Stopping

We show that the value function of a singular stochastic control problem is equal to the integral of the value function of an associated optimal stopping problem. The connection is proved for a general class of diffusions using the method of viscosity solutions.