This paper addresses the robust counterparts of optimization problems containing sums of maxima of linear functions and proposes several reformulations. These problems include many practical problems, e.g. problems with sums of absolute values, and arise when taking the robust counterpart of a...

We propose a method to estimate both whether there is an overall infrastructure shortage and the optimal share of infrastructure in gross fixed capital formation (GFCF). This is based on a two-gap model and linear programming, and is illustrated with the case of Mexico (1950-1985). The results...

We provide results for an efficient analytical valuation of partial moments of the multivariate Gaussian distribution over convex polyhedrons to aid the solution, sensitivity analysis and structural analysis of a large number of two-stage resource acquisition and allocation problems. These...

This article uses a sequentialized experimental design to select simulation input combinations for global optimization, based on Kriging (also called Gaussian process or spatial correlation modeling); this Kriging is used to analyze the input/output data of the simulation model (computer code)....

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...

Solving optimization problems becomes a central theme not only on operational research but also on several research areas like robotic, medicine, economic etc. The number of support decision problems that can be formalized as an optimization problem is growing rapidly. This study represents a...