We study the stochastic machine replenishment problem, which is a canonical special case of closed multiclass queuing systems in Markov decision theory. The problem models the scheduling of processor repairs in a multiprocessor system in which one repair can be made at a time and the goal is to maximize system utilization. We analyze the performance of a natural greedy index policy for this pro...

This paper studies the approximation of pseudo-Boolean functions by linear functions and more generally by functions of (at most) a specified degree. Here a pseudo-Boolean function means a real valued function defined on {0, 1} n, and its degree is that of the unique multilinear polynomial that expresses it; linear functions are those of degree at most one. The approximation consists in choosin...

in this paper, we propose the chebyshev wavelet approximation for the numerical solution of a class of integro-differential equation which describes the charged particle motion for certain configurations of oscillating magnetic fields. we show that the chebyshev approximation transform an integral equation to an explicit system of linear algebraic equations. illustrative examples are included t...

We formulate the well-known economic lot scheduling problem (ELSP) with sequence dependent setup times and costs as a semi-Markov decision process. Using an affine approximation of the bias function, we obtain a semi-infinite linear program determining a lower bound for the minimum average total cost rate. The solution of this problem is directly used in a price-directed dynamic heuristic to de...

The aim of this paper is to compare various real estate valuation models and the manner in which they take into account environmental variables. The reference model is taken to be a standard linear regression model including ordinal variables to measure environmental quality. This type of model is widely used. It is first compared to linear models which incorporate environmental quality notes e...

We consider the variant of the minimum vertex cover problem in which we require that the cover induces a connected subgraph. We give new approximation results for this problem in dense graphs, in which either the minimum or the average degree is linear. In particular, we prove tight parameterized upper bounds on the approximation returned by Savage’s algorithm, and extend a vertex cover algorit...

This paper studies the discrete-time sampled-data approximation of the input-constrained finite-horizon linear quadratic regulator problem. Explicit estimates for the error in the performance index rendered by the solution of a discrete-time approximation are provided. This result can be used to evaluate the level of sub-optimality of the sampled-data solution corresponding to a given discretis...

Restricted non-linear approximation is a type of N-term approximation where a measure ν on the index set (rather than the counting measure) is used to control the number of terms in the approximation. We show that embeddings for restricted non-linear approximation spaces in terms of weighted Lorentz sequence spaces are equivalent to Jackson and Bernstein type inequalities, and also to the upper...