Ce document est publié dans l'intention de rendre accessibles les résultats préliminaires de la recherche effectuée au CIRANO, afin de susciter des échanges et des suggestions. Les idées et les opinions émises sont sous l'unique responsabilité des auteurs, et ne représentent pas nécessairement les positions du CIRANO ou de ses partenaires. This paper presents preliminary research carried out at...

Methods which do not use any derivative information are becoming popular among researchers, since they allow to solve many real-world engineering problems. Such problems are frequently characterized by the presence of discrete variables, which can further complicate the optimization process. In this paper, we propose derivative-free algorithms for solving continuously differentiable Mixed Integ...

Virtual machine introspection (VMI) describes the method of monitoring, analyzing, and manipulating the state of a virtual machine from the hypervisor level. This lends itself to many security applications, though they all share a single fundamental challenge: One must address the fact that the hypervisor has no semantic knowledge about what the system state means (e. g., where key data structu...

Monte Carlo (MC) methods have proved to be flexible, robust and very useful techniques in computational finance. Several studies have investigated ways to achieve greater efficiency of such methods for serial computers. In this paper, we concentrate on the parallelization potentials of the MC methods. While MC is generally thought to be “embarrassingly parallel”, the results eventually depend o...

In this work, two multi-step derivative-free iterative methods are presented for solving system of nonlinear equations. The new methods have high computational efficiency and low computational cost. The order of convergence of the new methods is proved by a development of an inverse first-order divided difference operator. The computational efficiency is compared with the existing methods. Nume...

This thesis is divided into two parts that each is concerned with a specific problem. The problem under consideration in the first part is to find suitable graph representations, abstractions, cost measures and algorithms for calculating placements of unmanned aerial vehicles (UAVs) such that they can keep one or several static targets under constant surveillance. Each target is kept under surv...

A new method for derivative-free optimization is presented. It is designed for solving problems in which the objective function is smooth and the number of variables is moderate, but the gradient is not available. The method generates a model that interpolates the objective function at a set of sample points, and uses trust regions to promote convergence. The step-generation subproblem ensures ...

In this paper, a new optimally convergent eighth-order class of three-step without memory methods is suggested. We here pursue derivative-free algorithms, i.e., algorithms requiring only the ability to evaluate the (objective) function. Since the types of problems that these algorithms can solve are extremely diverse in nature. The analysis of convergence shows that each derivative-free method ...

There have been interesting recent developments in methods for solving optimization problems without making use of derivative (sensitivity) information. While calculus based methods that employ derivative information can be extremely eecient and very eeec-tive, they are not applicable to all MDO problems, for instance, when the function to be optimized is nondiierentiable, when sensitivity info...