Abstract. Simple continuous estimation of distribution algorithms are applied to a benchmark real-world set of problems: packing circles in a square. Although the algorithms tested are very simple and contain mini-mal parameters, it is found that performance varies surprisingly with pa-rameter settings, specifically the population size. Furthermore, the pop-ulation size that produced the best performance is an order of magnitude larger that the values typically used in the literature. The best results in the study improve on previous results with EDAs on this benchmark, but the main conclusion of the paper is that algorithm parameter settings need to be carefully considered when applying metaheuristic algorithms to different problems and wh...
Abstract. We consider the average case behavior of one-dmensional bin paekmg algorithms in the case ...
Often, Estimation-of-Distribution Algorithms (EDAs) are praised for their ability to optimize a broa...
The successful application of estimation of distribution algorithms (EDAs) to solve different kinds...
Simple continuous estimation of distribution algorithms are applied to a benchmark real-world set of...
We consider a scalable problem that has strong ties with real-world problems, can be compactly formu...
This chapter serves as an introduction to estimation of distribution algorithms (EDAs). Estimation o...
Conducting research in order to know the range of problems in which a search algorithm is effective...
Abstract — This paper presents a framework for the theoret-ical analysis of Estimation of Distributi...
This paper presents a study based on the empirical results of the average first hitting time of Esti...
In this paper, we treat the identification of some of the problems that are relevant for the improve...
Research into the dynamics of Genetic Algorithms (GAs) has led to the ¯eld of Estimation{of{Distribu...
This paper describes Mateda-2.0, a MATLAB package for estimation of distribution algorithms (EDAs). ...
Estimation of distribution algorithm (EDA) is an efficient population-based stochastic search techni...
This paper describes Mateda-2.0, a MATLAB package for estimation of distribution algorithms (EDAs). ...
EDA tools employ randomized algorithms for their favorable properties. Deterministic algorithms have...
Abstract. We consider the average case behavior of one-dmensional bin paekmg algorithms in the case ...
Often, Estimation-of-Distribution Algorithms (EDAs) are praised for their ability to optimize a broa...
The successful application of estimation of distribution algorithms (EDAs) to solve different kinds...
Simple continuous estimation of distribution algorithms are applied to a benchmark real-world set of...
We consider a scalable problem that has strong ties with real-world problems, can be compactly formu...
This chapter serves as an introduction to estimation of distribution algorithms (EDAs). Estimation o...
Conducting research in order to know the range of problems in which a search algorithm is effective...
Abstract — This paper presents a framework for the theoret-ical analysis of Estimation of Distributi...
This paper presents a study based on the empirical results of the average first hitting time of Esti...
In this paper, we treat the identification of some of the problems that are relevant for the improve...
Research into the dynamics of Genetic Algorithms (GAs) has led to the ¯eld of Estimation{of{Distribu...
This paper describes Mateda-2.0, a MATLAB package for estimation of distribution algorithms (EDAs). ...
Estimation of distribution algorithm (EDA) is an efficient population-based stochastic search techni...
This paper describes Mateda-2.0, a MATLAB package for estimation of distribution algorithms (EDAs). ...
EDA tools employ randomized algorithms for their favorable properties. Deterministic algorithms have...
Abstract. We consider the average case behavior of one-dmensional bin paekmg algorithms in the case ...
Often, Estimation-of-Distribution Algorithms (EDAs) are praised for their ability to optimize a broa...
The successful application of estimation of distribution algorithms (EDAs) to solve different kinds...