This discussion paper considers the use of stochastic algorithms for solving global optimisation problems in which function evaluations are subject to random noise. An idea is outlined for discussion at the forthcoming Stochastic Global Optimisation 2001 workshop in Hanmer in June; we propose that a noisy version of pure random search be studied.2 page(s
In this report we describe a set of numerical experiments carried out in order to appreciate the mer...
This dissertation considers several common notions of complexity that arise in large-scale systems o...
A stochastic method for global optimization is described and evaluated. The method involves a combin...
We discuss the noisy optimisation problem, in which function evaluations are subject to random noise...
Abstract. We consider the unconstrained optimization of a function when each function evaluation is ...
We consider the unconstrained optimization of a function when each function evaluation is subject to...
Global optimisation of unknown noisy functions is a daunting task that appears in domains ranging fr...
International audienceWe consider the problem of the global minimization of a function observed with...
We examine the conventional wisdom that commends the use of directe search methods in the presence o...
In this paper we propose a modified version of the simulated annealing algorithm for solving a stoch...
A multitude of heuristic stochastic optimization algorithms have been described in literature to obt...
Many optimization tasks must be handled in noisy environments, where the exact evaluation of a solut...
Stochastic optimization algorithms have been growing rapidly in popularity over the last decade or t...
One of the significant challenges when solving optimization problems is addressing possible inaccura...
This book presents the main methodological and theoretical developments in stochastic global optimiz...
In this report we describe a set of numerical experiments carried out in order to appreciate the mer...
This dissertation considers several common notions of complexity that arise in large-scale systems o...
A stochastic method for global optimization is described and evaluated. The method involves a combin...
We discuss the noisy optimisation problem, in which function evaluations are subject to random noise...
Abstract. We consider the unconstrained optimization of a function when each function evaluation is ...
We consider the unconstrained optimization of a function when each function evaluation is subject to...
Global optimisation of unknown noisy functions is a daunting task that appears in domains ranging fr...
International audienceWe consider the problem of the global minimization of a function observed with...
We examine the conventional wisdom that commends the use of directe search methods in the presence o...
In this paper we propose a modified version of the simulated annealing algorithm for solving a stoch...
A multitude of heuristic stochastic optimization algorithms have been described in literature to obt...
Many optimization tasks must be handled in noisy environments, where the exact evaluation of a solut...
Stochastic optimization algorithms have been growing rapidly in popularity over the last decade or t...
One of the significant challenges when solving optimization problems is addressing possible inaccura...
This book presents the main methodological and theoretical developments in stochastic global optimiz...
In this report we describe a set of numerical experiments carried out in order to appreciate the mer...
This dissertation considers several common notions of complexity that arise in large-scale systems o...
A stochastic method for global optimization is described and evaluated. The method involves a combin...