An existence and uniqueness theorem for one optimal control problem

In this paper we investigate the existence and uniqueness for an optimal control problem with processes described by a quasilinear parabolic equation with controls in coefficients and the right side of this equation.     

An existence theorem for systems of boundary value problems

We prove an existence theorem for , , in , using the shooting method. The function is supposed to be asymptotically linear.

     

An existence theorem for optimal controls

An existence theorem is given based on a criterion ensuring compactness of the controls in the metric corresponding to convergence in measure.This research was performed under NSF Grant No. GP-7372     

On the existence of an optimal feedback control for stochastic systems

We prove the existence of an optimal control for systems of stochastic differential equations without solving the Bellman dynamic programming equation. Instead, we use direct methods for solving extremal problems.     

An existence theorem for packing problems with implications for the computation of optimal machine schedules

Motivated by a job-shop problem we ask on which conditions n intervals v_i: with given lengths d_i , can be arranged non-overlapping on the real axis, so that every v_i is placed in a given frame [f_i s_i ].We prove a necessary and sufficient criterion analogous to the “marriage theorem” but with an additional monotony in the ages. Using this criterion we can accelerate branch and bound algorithms for job-shop scheduling by fixing partial sequences. For n = 2, the approved pair-combinatorics by Carlier and Pinson results. To show how the method works for other n. we derive the complete triple-combinatorics (n = 3: five sufficient criterions, which are necessary as a whole)     

Duality theorem for the stochastic optimal control problem

We prove a duality theorem for the stochastic optimal control problem with a convex cost function and show that the minimizer satisfies a class of forward–backward stochastic differential equations. As an application, we give an approach, from the duality theorem, to h$h$-path processes for diffusion processes.     

A theorem on existence of neighbouring trajectories satisfying a state constraint, with applications to optimal control

Simple directly verifiable conditions are derived under whichthere exists a state trajectory satisfying a specified stateconstraint. The conclusions differ from the kind of informationprovided by viability and invariance-type theorems, insofaras an estimate is provided of the distance (in the supremumnorm) of the state trajectory from a specified state trajectory,in terms of the degree to which the specified state trajectoryviolates the state constraint. The constructions involved inthe existence proof are related to ones previously employedby Soner to establish continuity properties of a value functionarising in infinite-horizon state-constrained optimal control,but the accompanying analysis contains refinements to ensurea sub-Lipschitz property of the value function considered here.It is expected that this existence result will have a numberof implications for systems theory and optimal control. Herewe show how it leads to a non-degenerate maximum principle forstate-constrained optimal-control problems, in situations wherethe standard necessary conditions give no useful informationabout minimizers. Email: rampazzo{at}pdmat1.unipd.it Email: r.vinter{at}ic.ac.uk     

An existence theorem for non-linear differential systems

Summary Systems of n non-linear, first-order differential equations, whose coefficient functions satisfy the Carathéodory Conditions, are studied. It is proved that, under certain conditions, the boundedness away from zero of a determinant of a type obtained by R. Conti is sufficient to insure the existence of solutions satisfying n boundary conditions assigned at as many as n points.     

An averaging theorem for two-point boundary value problems with applications to optimal control

An asymptotic result is obtained for a two-point boundary value problem for a vector system of nonlinear ordinary differential equations involving “fast” and “slow” inputs. The asymptotically limiting system is obtained by an averaging procedure. Using this result, an approximate analysis of the original system may be carried out by considering two lower-order systems each involving only one time scale. It is shown that some optimal control problems for systems with multiple time scales may be analyzed by this method.     

An existence and uniqueness theorem for an optimal inventory problem with forecasting

An existence and uniqueness theorem is proved for an optimal inventory problem with forecasting. The model assumes costs are fixed and that unsatisfied demand is lost. At each stage a forecast is obtained on the basis of which the decisionmaker has a known conditional probability distribution of demand. The theorem is a generalization of a result stated but not proved by White.     

Dynamic consistency for stochastic optimal control problems

For a sequence of dynamic optimization problems, we aim at discussing a notion of consistency over time. This notion can be informally introduced as follows. At the very first time step?t ₀, the decision maker formulates an optimization problem that yields optimal decision rules for all the forthcoming time steps?t ₀,t ₁,??,T; at the next time step?t ₁, he is able to formulate a new optimization problem starting at time?t ₁ that yields a new sequence of optimal decision rules. This process can be continued until the final time?T is reached. A?family of optimization problems formulated in this way is said to be dynamically consistent if the optimal strategies obtained when solving the original problem remain optimal for all subsequent problems. The notion of dynamic consistency, well-known in the field of economics, has been recently introduced in the context of risk measures, notably by Artzner et al. (Ann. Oper. Res. 152(1):5?C22, 2007) and studied in the stochastic programming framework by Shapiro (Oper. Res. Lett. 37(3):143?C147, 2009) and for Markov Decision Processes (MDP) by Ruszczynski (Math. Program. 125(2):235?C261, 2010). We here link this notion with the concept of ??state variable?? in MDP, and show that a significant class of dynamic optimization problems are dynamically consistent, provided that an adequate state variable is chosen.     

Particle methods for stochastic optimal control problems

When dealing with numerical solution of stochastic optimal control problems, stochastic dynamic programming is the natural framework. In order to try to overcome the so-called curse of dimensionality, the stochastic programming school promoted another approach based on scenario trees which can be seen as the combination of Monte Carlo sampling ideas on the one hand, and of a heuristic technique to handle causality (or nonanticipativeness) constraints on the other hand. However, if one considers that the solution of a stochastic optimal control problem is a feedback law which relates control to state variables, the numerical resolution of the optimization problem over a scenario tree should be completed by a feedback synthesis stage in which, at each time step of the scenario tree, control values at nodes are plotted against corresponding state values to provide a first discrete shape of this feedback law from which a continuous function can be finally inferred. From this point of view, the scenario tree approach faces an important difficulty: at the first time stages (close to the tree root), there are a few nodes (or Monte-Carlo particles), and therefore a relatively scarce amount of information to guess a feedback law, but this information is generally of a good quality (that is, viewed as a set of control value estimates for some particular state values, it has a small variance because the future of those nodes is rich enough); on the contrary, at the final time stages (near the tree leaves), the number of nodes increases but the variance gets large because the future of each node gets poor (and sometimes even deterministic). After this dilemma has been confirmed by numerical experiments, we have tried to derive new variational approaches. First of all, two different formulations of the essential constraint of nonanticipativeness are considered: one is called algebraic and the other one is called functional. Next, in both settings, we obtain optimality conditions for the corresponding optimal control problem. For the numerical resolution of those optimality conditions, an adaptive mesh discretization method is used in the state space in order to provide information for feedback synthesis. This mesh is naturally derived from a bunch of sample noise trajectories which need not to be put into the form of a tree prior to numerical resolution. In particular, an important consequence of this discrepancy with the scenario tree approach is that the same number of nodes (or points) are available from the beginning to the end of the time horizon. And this will be obtained without sacrifying the quality of the results (that is, the variance of the estimates). Results of experiments with a hydro-electric dam production management problem will be presented and will demonstrate the claimed improvements. A more realistic problem will also be presented in order to demonstrate the effectiveness of the method for high dimensional problems.     

Kolmogorov’s existence theorem for Markov processes inC* algebras

Given a family of transition probability functions between measure spaces and an initial distribution Kolmogorov’s existence theorem associates a unique Markov process on the product space. Here a canonical non-commutative analogue of this result is established for families of completely positive maps betweenC* algebras satisfying the Chapman-Kolmogorov equations. This could be the starting point for a theory of quantum Markov processes. Dedicated to the memory of Professor K G Ramanathan     

The existence results for obstacle optimal control problems

This paper is concerned with the existence of an optimal control problem for a quasi-linear elliptic obstacle variational inequality in which the obstacle is taken as the control. Firstly, we get some existence results under the assumption of the leading operator of the variational inequality with a monotone type mapping in Section 2. In Section 3, as an application, without the assumption of the monotone type mapping for the leading operator of the variational inequality, we prove that the leading operator of the variational inequality is a monotone type mapping. Existence of the optimal obstacle is proved. The method used here is different from [Y.Y. Zhou, X.Q. Yang, K.L. Teo, The existence results for optimal control problems governed by a variational inequality, J. Math. Anal. Appl. 321 (2006) 595-608].     

An existence theorem for systems of linear equations

Given is a constructive proof of the following theorem: A system of linear equations has a [nonnegative] solution if and only if each system constructed by replacing each equation by one of the two associated inequalities has a [nonnegative] solution.     

An existence theorem for some semilinear elliptic systems

An existence theorem is obtained for a class of semilinear, second order, uniformly elliptic systems obtained formally from a variational principle and modeled on nonlinear Helmholtz systems. Superlinear growth of the nonlinear term precludes application of standard methods to these systems. Indeed, we permit very rapid growth of the nonlinear term, so the underlying functional is not defined on the Hilbert space within which a solution is naturally sought. Mollification of the nonlinear term nonetheless results in the resulting functional satisfying the Palais-Smale condition; critical points are determined by solution of a dynamical system. The limit of vanishing mollification then produces a weak solution of the original problem.     

An existence result for optimal economic growth problems

An existence result for optimal control problems of Lagrange type with unbounded time domain is derived very directly from a corresponding result for problems with bounded time domain. This subsumes the main existence result of R. F. Baum ¦J. Optim. Theory Appl.19 (1976), 89–116¦ and has the existence results for optimal economic growth problems of S.-I. Takekuma ¦J. Math. Econom.7 (1980), 193–208¦ and M. J. P. Magill ¦Econometrica49 (1981), 679–711; J. Math. Anal. Appl.82 (1981), 66–74¦ as simple corollaries. In addition, a new notion of uniform integrability is used, which coincides with the classical notion if the time domain is bounded.