Telecommunication networks are characterised by a complex group of intermediaries and each one of them faces two types of operational costs: transmission costs and delivery cost. This scheme allows the operator to evaluate the market structure and to perform the telecommunication service. The...

This paper proposes a novel method of global optimization based on cuckoo-host co-evaluation. It also develops a Fortran-77 code for the algorithm. The algorithm has been tested on 96 benchmark functions (of which the results of 30 relatively harder problems have been reported). The proposed...

In this contribution we propose a dynamic tracking error problem and we consider the problem of monitoring at discrete point the shortfall of the portfolio below a set of given reference levels of wealth. We formulate and solve the resulting dynamic optimization problem using stochastic...

We propose a new class of knapsack problems by assiuning that the sizes of the items to be put into a knapsack are known to be elements 0f a given subset S of the positive integers Z'^. The set S is treated as a parameter. We show that the family of knapsack problems obtained by varying the...

Economists who want to numerically approximate an elaborate dynamic stochastic programming problem (DSPP), either for structural estimation or policy evaluation purposes, are often confined by the curse of dimensionality: richer models with various state and control variables cannot be solved on...

This paper proposes a new methodology to solve partially observed inventory problems. Generally, these problems have infinitedimensional states that are conditional distribution of the inventory level. Our methodology involves linearizing the state transitions via unnormalized probabilities. It...

The set covering problem is an NP-hard combinatorial optimization problem that arises in applications ranging from crew scheduling in airlines to driver scheduling in public mass transport. In this paper we analyze search space characteristics of a widely used set of benchmark instances through...

A divide-and-conquer algorithm for exploiting policy function monotonicity is proposed and analyzed. To compute a discrete problem with n states and n choices, the algorithm requires at most 5n log2(n)n function evaluations and so is O(n log2 n). In contrast, existing methods for non-concave...

We introduce a novel scheme based on a blending of Fourier-Motzkin elimination (FME) and adjustable robust optimization techniques to compute the maximum volume inscribed ellipsoid (MVE) in a polytopic projection. It is well-known that deriving an explicit description of a projected polytope is...

We present a computationally effective method of solving regular linear dynamic systems based on Schur decomposition. One of the advantage of presented method is possibility of problem dimension reduction. This allows for efficient solution of models with very large set of endogenous variables...