BOA: The Bayesian Optimization Algorithm

In this paper, an algorithm based on the concepts of genetic algorithms that uses an estimation of the joint distribution of promising solutions in order to generate new candidate solutions is proposed. The proposed algorithm is called the Bayesian optimization algorithm (BOA). To estimate the distribution of promising solutions, techniques for modeling multivariate data by Bayesian networks are used. The proposed algorithm identifies, reproduces and mixes building blocks up to a specified order. It is independent of the ordering of the variables in the strings representing the solutions. Moreover, prior information about the problem can be incorporated into the algorithm. However, the prior information is not essential. Preliminary experiments show that the BOA outperforms the simple genetic algorithm even on decomposable functions with tight building blocks as the problem size grows. 1 Introduction Recently, there has been a growing interest in optimization methods that explicitly m..