Finding all minimal elements of a finite partially ordered set by genetic algorithm with a prescribed probability (Q428481)
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scientific article; zbMATH DE number 6049055
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Finding all minimal elements of a finite partially ordered set by genetic algorithm with a prescribed probability |
scientific article; zbMATH DE number 6049055 |
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Finding all minimal elements of a finite partially ordered set by genetic algorithm with a prescribed probability (English)
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22 June 2012
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A finite multi-objective optimization problem is considered. A version of the simple genetic algorithm is applied to find all non-dominated solutions. An upper bound for the number of iterations needed to solve the problem with the prescribed accuracy is evaluated. The analysis is based on the Markov chain model adapted to the considered search process.
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genetic algorithms
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Markov chain
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stopping criteria
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