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Multiobjective Estimation of Distribution Algorithm Based on Joint Modeling of Objectives and Variables
2014
IEEE Transactions on Evolutionary Computation
This paper proposes a new multi-objective estimation of distribution algorithm (EDA) based on joint probabilistic modeling of objectives and variables. This EDA uses the multidimensional Bayesian network as its probabilistic model. In this way it can capture the dependencies between objectives, variables and objectives, as well as the dependencies learnt between variables in other Bayesian network-based EDAs. This model leads to a problem decomposition that helps the proposed algorithm to find
doi:10.1109/tevc.2013.2281524
fatcat:4s3ahirmsjavzclu4ranf6tyny