16 citations · 31 across the 6 of their papers we have counts for
8 papers · 1 filter
iBOA: The Incremental Bayesian Optimization Algorithm
Martin Pelikan, Kumara Sastry, David E. Goldberg
This paper proposes the incremental Bayesian optimization algorithm (iBOA), which modifies standard BOA by removing the population of solutions and using incremental updates of the…
Analysis of Estimation of Distribution Algorithms and Genetic Algorithms on NK Landscapes
Martin Pelikan
This study analyzes performance of several genetic and evolutionary algorithms on randomly generated NK fitness landscapes with various values of n and k. A large number of NK prob…
Decomposable Problems, Niching, and Scalability of Multiobjective Estimation of Distribution Algorithms
Kumara Sastry, Martin Pelikan, David E. Goldberg
The paper analyzes the scalability of multiobjective estimation of distribution algorithms (MOEDAs) on a class of boundedly-difficult additively-separable multiobjective optimizati…
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…
Parallel Mixed Bayesian Optimization Algorithm: A Scaleup Analysis
Jiri Ocenasek, Martin Pelikan
Estimation of Distribution Algorithms have been proposed as a new paradigm for evolutionary optimization. This paper focuses on the parallelization of Estimation of Distribution Al…