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Everything about Estimation of distribution algorithm

Family of stochastic optimization methods

Estimation of distribution algorithms (EDAs), sometimes called probabilistic model-building genetic algorithms (PMBGAs), are stochastic optimization methods that guide the search for the optimum by building and sampling explicit probabilistic models of promising candidate solutions. Optimization is viewed as a series of incremental updates of a probabilistic model, starting with the model encoding an uninformative prior over admissible solutions and ending with the model that generates only the global optima. Wikipedia →

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  1. Read the overview: Estimation of distribution algorithmA 5-minute orientation
  2. Skim a recent paper: An improved differential evolution by hybridizing with estimation-of-distribution algorithmInfluential work since 2022
  3. Pick up a classic book: Software EngineeringThe most-reprinted book on the subject
  4. Read the landmark paper: Hybrid estimation of distribution algorithm for global optimizationCited 80 times
  5. Go sideways: Variable eliminationA closely related topic
  6. Go sideways: Stochastic chains with memory of variable lengthA closely related topic

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