Linkage Problem, Distribution Estimation, and Bayesian Networks

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Elitism-based compact genetic algorithms (2003, methodology): “In the context of GAs, ISG systems are frequently employed as test cases in the study of GAs because they exhibit symmetry and a large number of plateaus [ 30 ], [31].”
An Evolutionary Algorithm for Large-Scale Sparse Multiobjective Optimization Problems (2020, methodology): “…search space of LOPs, they cannot be easily solved by general evolutionary algorithms, hence some novel techniques have been adopted to tackle speciﬁc types of LOPs, such as variable interaction analysis [32]–[34], linkage learning [35], and random embedding-based Bayesian optimization [36], [37].”
Evolvable Neuronal Paths: A Novel Basis for Information and Search in the Brain (2011, methodology): “As far as we are aware one of the goals of EDAs was to remove ‘‘arbitrary’’ operators such as mutation and crossover.”
The Parallel Bayesian Optimization Algorithm (2000, methodology): “The Bayesian Optimization Algorithm incorporates methods for learning Bayesian networks and uses these to model the promising solutions and generate new ones.”