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- ItemConsidering copositivity locally(Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik, 2014) Dickinson, Peter J.C.; Hildebrand, RolandLet $A$ be an element of the copositive cone $coposn$. A zero $vu$ of $A$ is a nonnegative vector whose elements sum up to one and such that $vu^TAvu = 0$. The support of $vu$ is the index set $Suppvu subset 1,dots,n$ corresponding to the nonzero entries of $vu$. A zero $vu$ of $A$ is called minimal if there does not exist another zero $vv$ of $A$ such that its support $Suppvv$ is a strict subset of $Suppvu$. Our main result is a characterization of the cone of feasible directions at $A$, i.e., the convex cone $VarKA$ of real symmetric $n times n$ matrices $B$ such that there exists $delta > 0$ satisfying $A + delta B in coposn$. This cone is described by a set of linear inequalities on the elements of $B$ constructed from the set of zeros of $A$ and their supports. This characterization furnishes descriptions of the minimal face of $A$ in $coposn$, and of the minimal exposed face of $A$ in $coposn$, by sets of linear equalities and inequalities constructed from the set of minimal zeros of $A$ and their supports. In particular, we can check whether $A$ lies on an extreme ray of $coposn$ by examining the solution set of a system of linear equations. In addition, we deduce a simple necessary and sufficient condition on the irreducibility of $A$ with respect to a copositive matrix $C$. Here $A$ is called irreducible with respect to $C$ if for all $delta > 0$ we have $A - delta C notin coposn$.
- ItemMinimal zeros of copositive matrices(Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik, 2014) Hildebrand, RolandLet A be an element of the copositive cone Cn. A zero u of A is a nonzero nonnegative vector such that uT Au = 0. The support of u is the index set supp u c {1,..., n}corresponding to the positive entries of u. A zero u of A is called minimal if there does not exist another zero v of A such that its support supp v is a strict subset of supp u. We investigate the properties of minimal zeros of copositive matrices and their supports. Special attention is devoted to copositive matrices which are irreducible with respect to the cone S+(n) of positive semi-definite matrices, i.e., matrices which cannot be written as a sum of a copositive and a nonzero positive semi-definite matrix. We give a necessary and sufficient condition for irreducibility of a matrix A with respect to S+(n) in terms of its minimal zeros. A similar condition is given for the irreducibility with respect to the cone Nn of entry-wise nonnegative matrices. For n = 5 matrices which are irreducible respect to both S+(5) and N5 are extremal. For n = 6 a list of candidate combinations of supports of minimal zeros which an exceptional extremal matrix can have is provided.
- ItemOptimal stopping via pathwise dual empirical maximisation(Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik, 2014) Belomestny, Denis; Hildebrand, Roland; Schoenmakers, John G.M.The optimal stopping problem arising in the pricing of American options can be tackled by the so called dual martingale approach. In this approach, a dual problem is formulated over the space of martingales. A feasible solution of the dual problem yields an upper bound for the solution of the original primal problem. In practice, the optimization is performed over a finite-dimensional subspace of martingales. A sample of paths of the underlying stochastic process is produced by a Monte-Carlo simulation, and the expectation is replaced by the empirical mean. As a rule the resulting optimization problem, which can be written as a linear program, yields a martingale such that the variance of the obtained estimator can be large. In order to decrease this variance, a penalizing term can be added to the objective function of the path-wise optimization problem. In this paper, we provide a rigorous analysis of the optimization problems obtained by adding different penalty functions. In particular, a convergence analysis implies that it is better to minimize the empirical maximum instead of the empirical mean. Numerical simulations confirm the variance reduction effect of the new approach.
- ItemSpectrahedral cones generated by rank 1 matrices(Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik, 2014) Hildebrand, Roland[no abstract available]
- ItemClosed-loop optimal experiment design: Solution via moment extension(Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik, 2013) Hildebrand, Roland; Gevers, Michel; Solari, GabrielWe consider optimal experiment design for parametric prediction error system identification of linear time-invariant multiple-input multiple-output (MIMO) systems in closed-loop when the true system is in the model set. The optimization is performed jointly over the controller and the spectrum of the external excitation, which can be reparametrized as a joint spectral density matrix. We have shown in [18] that the optimal solution consists of first computing a finite set of generalized moments of this spectrum as the solution of a semi-definite program. A second step then consists of constructing a spectrum that matches this finite set of optimal moments and satisfies some constraints due to the particular closed-loop nature of the optimization problem. This problem can be seen as a moment extension problem under constraints. Here we first show that the so-called central extension always satisfies these constraints, leading to a constructive procedure for the optimal controller and excitation spectrum.We then show that, using this central extension, one can construct a broader set of parametrized optimal solutions that also satisfy the constraints; the additional degrees of freedom can then be used to achieve additional objectives. Finally, our new solution method for the MIMO case allows us to considerably simplify the proofs given in [18] for the single-input single-output case.
- ItemRegression based duality approach to optimal control with application to hydro electricity storage(Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik, 2016) Hildebrand, Roland; Schoenmakers, John; Zhang, Jianing; Dickmann, FabianIn this paper we consider the problem of optimal control of stochastic processes. We employ the dual martingale method brought forward in [Brown, Smith, and Sun, 2010]. The martingale constituting the solution of the dual problem is determined by linear regression within a Monte-Carlo approach. We apply the solution algorithm to a model of a hydro electricity storage and production system coupled with a model of the electricity wholesale market.