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m clean up, replaced: citeseerx=10.1.1.47.6497}}</ref> factorizes the joint probability distribution in a chain-like model representing successive dependencies between variables. It finds a permutation of the decision variables, <math>r : i \mapst |
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==Other==
* Probability collectives (PC)<ref>{{cite journal|last1=WOLPERT|first1=DAVID H.|title=Advances in Distributed Optimization Using Probability Collectives|last2=STRAUSS|first2=CHARLIE E. M.|last3=RAJNARAYAN|first3=DEV|journal=Advances in Complex Systems|date=December 2006|volume=09|issue=4|pages=383–436|doi=10.1142/S0219525906000884|citeseerx=10.1.1.154.6395}}</ref><ref>{{cite journal|last1=Pelikan|first1=Martin|last2=Goldberg|first2=David E.|last3=Lobo|first3=Fernando G.|title=A Survey of Optimization by Building and Using Probabilistic Models|journal=Computational Optimization and Applications|date=2002|volume=21|issue=1|pages=5–20|doi=10.1023/A:1013500812258}}</ref>
* Hill climbing with learning (HCwL)<ref>{{Cite journal|last=Rudlof|first=Stephan|last2=Köppen|first2=Mario|date=1997|title=Stochastic Hill Climbing with Learning by Vectors of Normal Distributions|
* Estimation of multivariate normal algorithm (EMNA){{Citation needed|date=June 2018}}
* Estimation of Bayesian networks algorithm (EBNA){{Citation needed|date=June 2018}}
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