A multitude of heuristic stochastic optimization algorithms have been described in literature to obtain good solutions of the box-constrained global optimization problem often with a limit on the number of used function evaluations. In the larger question of which algorithms behave well on which type of instances, our focus is here on the benchmarking of the behavior of algorithms by applying experiments on test instances. We argue that a good minimum performance benchmark is due to pure random search; i.e. algorithms should do better. We introduce the concept of the cumulative<br/>distribution function of the record value as a measure with the benchmark of pure random search and the idea of algorithms being dominated by others. The concept...
We consider a variety of issues that arise when designing and analyzing computational experiments fo...
Abstract. Improving Hit-and-Run is a random search algorithm for global optimization that at each it...
AbstractIn this paper, we establish some bounds for the probability that stimulated annealing produc...
A multitude of heuristic stochastic optimization algorithms have been described in literature to obt...
This discussion paper for the SGO 2001 Workshop considers the process of investigating stochastic gl...
Stochastic optimization algorithms have been growing rapidly in popularity over the last decade or t...
This discussion paper considers the use of stochastic algorithms for solving global optimisation pro...
This book presents the main methodological and theoretical developments in stochastic global optimiz...
Heuristic algorithms are often difficult to analyse theoretically; this holds in particular for adva...
Controlled Random Search (CRS) is a simple population based algorithm which despite its attractivene...
A stochastic method for global optimization is described and evaluated. The method involves a combin...
It is difficult to evaluate a random search algorithms, because regardless of a chosen method of eff...
We examine the conventional wisdom that commends the use of directe search methods in the presence o...
Optimization by stochastic gradient descent is an important component of many large-scale machine le...
In this paper several probabilistic search techniques are developed for global optimization under th...
We consider a variety of issues that arise when designing and analyzing computational experiments fo...
Abstract. Improving Hit-and-Run is a random search algorithm for global optimization that at each it...
AbstractIn this paper, we establish some bounds for the probability that stimulated annealing produc...
A multitude of heuristic stochastic optimization algorithms have been described in literature to obt...
This discussion paper for the SGO 2001 Workshop considers the process of investigating stochastic gl...
Stochastic optimization algorithms have been growing rapidly in popularity over the last decade or t...
This discussion paper considers the use of stochastic algorithms for solving global optimisation pro...
This book presents the main methodological and theoretical developments in stochastic global optimiz...
Heuristic algorithms are often difficult to analyse theoretically; this holds in particular for adva...
Controlled Random Search (CRS) is a simple population based algorithm which despite its attractivene...
A stochastic method for global optimization is described and evaluated. The method involves a combin...
It is difficult to evaluate a random search algorithms, because regardless of a chosen method of eff...
We examine the conventional wisdom that commends the use of directe search methods in the presence o...
Optimization by stochastic gradient descent is an important component of many large-scale machine le...
In this paper several probabilistic search techniques are developed for global optimization under th...
We consider a variety of issues that arise when designing and analyzing computational experiments fo...
Abstract. Improving Hit-and-Run is a random search algorithm for global optimization that at each it...
AbstractIn this paper, we establish some bounds for the probability that stimulated annealing produc...