We present a convex conic relaxation for a problem of maximising an indefinite quadratic form over a set of convex constraints on the squared variables. We show that for all these problems we get at least 12/37 relative accuracy of the approximation. In the second part of the paper we derive the...

In this paper we study the concepts of equilibrium and optimum in static transportation networks with elastic and non-elastic demands. The main mathematical tool of our paper is the theory of variational inequalities. We demonstrate that this theory is useful for proving the existence theorems....

New results in the asymptotic theory of Markov processes are applied to analysis of the long-run behaviour exhibited by optimal growth models with unbounded productivity shock. The techniques developed here are geometrically intuitive, and are shown to imply global stability for a popular model...

This paper develops a formal framework based on multivariate spectral techniques for assessing the performance of multivariate dynamic models whose solution is approximated through simulation. The approach is especially suitable for models that focus on a particular frequency range , such as...

This paper develops a formal framework based on multivariate spectral techniques for assesssing the performance of multivariate dynamic models whose solution is approximated through simulation. The approach is especially suitable for models that focus on a particular frequency range , such as...

This paper develops an extension of the Riemann sum techniques of Philippe (1997b) in the setup of MCMCC algorithms. It shows that the technique applies equally well to the output of these algorithms, with similar speeds of convergence which improve upon the regular estimator. The restriction on...

In this paper we consider a labor constrained scheduling problem (LCSP) which is a simplification of a practical problem arising in industry. Jobs are subject to precedence constraints and have specified processing times. Moreover, for each job the labor requirements varies as the job is...

In this paper we study Markov Decision Process (MDP) problems with the restriction that at decision epochs only a finite number of given Markovian decision rules may be applied. The elements of the finite set of allowed decision rules should be mixed to improve the performance. The set of...

In this paper we study Markov Decision Process (MDP) problems with the restriction that at decision epochs only a finite number of given Markovian decision rules may be applied. The elements of the finite set of allowed decision rules should be mixed to improve the performance. The set of...