Titlebook: Dynamic Optimization; Deterministic and St Karl Hinderer,Ulrich Rieder,Michael Stieglitz Textbook 2016 Springer International Publishing AG

lymphedema

Prostaglandins

Introduction and Organization of the Book,In this treatise we deal with optimization problems whose objective functions show a sequential structure and hence are amenable to sequential methods. The corresponding field mostly goes by the name .. Other names are . and .. In order to avoid possible confusion with programming in computer science we speak of ..

投票

規(guī)章

Examples of Deterministic Dynamic ProgramsIn this chapter we explicitly solve the following: optimal routing of a freighter, a production-inventory problem with linear costs, allocation and linear-quadratic problems and a scheduling problem. Then we discuss some further models: DPs with random length of periods and with random termination.

螢火蟲

Absorbing Dynamic Programs and Acyclic NetworksWe study the problem of maximizing the sum of discounted rewards, earned not over a fixed number of periods, but until the decision process enters a given absorbing set. The basic theorem for absorbing DPs is derived. Moreover, we show how absorbing DPs can be used to find cost-minimal subpaths in acyclic networks.

OFF

Concavity and Convexity of the Value FunctionsHere we deal with the following questions, assuming that the functions under consideration are defined on convex sets or on a non-degenerate discrete interval.

FANG

攝取

BLANK

Control Models with DisturbancesIn this chapter we introduce control models with finite and i.i.d. disturbances. We prove the reward iteration and derive the basic solution techniques: value iteration and optimality criterion.

易改變

Markovian Decision Processes with Finite Transition LawFirstly we introduce MDPs with finite state spaces, prove the reward iteration and derive the basic solution techniques: value iteration and optimality criterion. Then MDPs with finite transition law are considered. There the set of reachable states is finite.