Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Imen Zghidi"'
Publikováno v:
Constraints. 23:196-209
Chance constraints are a major modeling tool for problems under uncertainty. We summarize the basic modeling ingredients of uncertain combinatorial problems and show how the Stochastic Constraint Satisfaction Problems formalism is able to support hig
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6dcade5cc0d354a24482428a0a4ddcdb
https://doi.org/10.1007/s10601-018-9283-8
https://doi.org/10.1007/s10601-018-9283-8
Publikováno v:
Annals of Mathematics and Artificial Intelligence. 83:165-181
In this paper, we propose a novel notion of statistical consistency for single-stage Stochastic Constraint Satisfaction Problems (SCSPs) in which some of the random variables’ support set is infinite. The essence of this novel notion of local consi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f88faab6e30f6748197017b5cb3bdd6a
https://doi.org/10.1007/s10472-018-9572-3
https://doi.org/10.1007/s10472-018-9572-3
Autor:
Imen, Zghidi
Publikováno v:
International Journal of Multicriteria Decision Making; 2021, Vol. 8 Issue: 3 p256-275, 20p
Autor:
Imen Zghidi
Publikováno v:
Constraints. 22:101-102
In most industrial contexts, decisions are made based on incomplete information. This is due to the fact that decision makers cannot be certain of the future behavior of factors that will affect the outcome resulting from various options under consid
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::38d40945f50bdbf1ad576d86b027239b
https://doi.org/10.1007/s10601-016-9264-8
https://doi.org/10.1007/s10601-016-9264-8
Publikováno v:
Annals of Mathematics and Artificial Intelligence. 83:183-183
The original version of this article unfortunately contained a mistake. The name “Abdelwahad Rebaii” should be corrected to “Abdelwaheb Rebai”.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::efeb9f42a21e1e64349511e5168973a3
https://doi.org/10.1007/s10472-018-9583-0
https://doi.org/10.1007/s10472-018-9583-0