11 citations · 13 across the 7 of their papers we have counts for
6 papers · 1 filter
Multiobjective hBOA, Clustering, and Scalability
Martin Pelikan, Kumara Sastry, David E. Goldberg
This paper describes a scalable algorithm for solving multiobjective decomposable problems by combining the hierarchical Bayesian optimization algorithm (hBOA) with the nondominate…
Scalability of Genetic Programming and Probabilistic Incremental Program Evolution
Radovan Ondas, Martin Pelikan, Kumara Sastry
This paper discusses scalability of standard genetic programming (GP) and the probabilistic incremental program evolution (PIPE). To investigate the need for both effective mixing…
Sub-structural Niching in Estimation of Distribution Algorithms
K. Sastry, H. A. Abbass, D. E. Goldberg +1
We propose a sub-structural niching method that fully exploits the problem decomposition capability of linkage-learning methods such as the estimation of distribution algorithms an…
Sub-Structural Niching in Non-Stationary Environments
K. Sastry, H. A. Abbass, D. E. Goldberg
Niching enables a genetic algorithm (GA) to maintain diversity in a population. It is particularly useful when the problem has multiple optima where the aim is to find all or as ma…
Designing Competent Mutation Operators via Probabilistic Model Building of Neighborhoods
Kumara Sastry, David E. Goldberg
This paper presents a competent selectomutative genetic algorithm (GA), that adapts linkage and solves hard problems quickly, reliably, and accurately. A probabilistic model buildi…
Efficiency Enhancement of Probabilistic Model Building Genetic Algorithms
Kumara Sastry, David E. Goldberg, Martin Pelikan
This paper presents two different efficiency-enhancement techniques for probabilistic model building genetic algorithms. The first technique proposes the use of a mutation operator…