Multi-objective optimization: Difference between revisions

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== A posteriori methods ==
A posteriori methods aim at producing all the Pareto optimal solutions or a representative subset of the Pareto optimal solutions. Most a posteriori methods fall into either one of the following three classes:
* [[Mathematical programming]]-based a posteriori methods where an algorithm is repeatedrun andrepeatedly, each run of the algorithm producesproducing one Pareto optimal solution;
* [[Evolutionary algorithm]]s where one run of the algorithm produces a set of Pareto optimal solutions;
* [[Deep learning]] methods where a model is first trained on a subset of solutions and then queried to provide other solutions on the Pareto front.