In many engineering problems, we face multi-objective optimization, with several objective functions f₁,...,fₙ. We want to provide the user with the Pareto set-a set of all possible solutions x which cannot be improved in all categories (i.e., for which for all j and for some j is impossible). The user should be able to select an appropriate trade-off between, say, cost and durability. We extend the general results about (verified) algorithmic computability of maxima locations to show that Pareto sets can also be computed.
@article{bwmeta1.element.bwnjournal-article-amcv19i3p369bwm, author = {Bogl\'arka G. T\'oth and Vladik Kreinovich}, title = {Verified methods for computing Pareto sets: General algorithmic analysis}, journal = {International Journal of Applied Mathematics and Computer Science}, volume = {19}, year = {2009}, pages = {369-380}, zbl = {1300.90041}, language = {en}, url = {http://dml.mathdoc.fr/item/bwmeta1.element.bwnjournal-article-amcv19i3p369bwm} }
Boglárka G. Tóth; Vladik Kreinovich. Verified methods for computing Pareto sets: General algorithmic analysis. International Journal of Applied Mathematics and Computer Science, Tome 19 (2009) pp. 369-380. http://gdmltest.u-ga.fr/item/bwmeta1.element.bwnjournal-article-amcv19i3p369bwm/
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