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Modeling uncertainties with chance constraints

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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 high-level declarative constructs that allow for ease of modeling of such problems in general. Then, we outline the different propagation methods for chance constraints. Finally, we identify some modeling subtleties that might arise when modeling with chance constraints.

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Authors and Affiliations

  1. MODILS Research Lab, FSEGS, Sfax University, Sfax, Tunisia

    Imen Zghidi & Abdelwaheb Rebaï

  2. CES, ENIS, Sfax University, Sfax, Tunisia

    Brahim Hnich

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  1. Imen Zghidi
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  2. Brahim Hnich
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  3. Abdelwaheb Rebaï
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Correspondence to Imen Zghidi.

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This article belongs to the Topical Collection: 20th Anniversary Issue

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Zghidi, I., Hnich, B. & Rebaï, A. Modeling uncertainties with chance constraints. Constraints 23, 196–209 (2018). https://doi.org/10.1007/s10601-018-9283-8

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  • DOI: https://doi.org/10.1007/s10601-018-9283-8

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