Sequential meta heuristic implementations for the irregular stock-cutting problem have highlighted a number of common problems. The implementation in this paper adopts a hybrid tabu search approach that incorporates two very different optimisation routines which utilise alternative neighborhoods...

A standard approach to duality in stochastic optimization problems with constraints in L(infinite) relies upon the Yosida-Hewitt theorem. We develop an alternative technique which employs only "elementary" means. The technique is based on an e-regularization of the original problem and on...

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...

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....

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...

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...

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...

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...

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...

A robust principal component analysis can be easily performed by computing the eigenvalues and eigenvectors of a robust estimator of the covariance or correlation matrix. In this paper the authors derive the influence functions and the corresponding asumptotic variances for these robust...