A survey on CP-AI-OR hybrids for decision making under uncertainty

B. Hnich, R. Rossi, S.A. Tarim, S. Prestwich

Research output: Chapter in Book/Report/Conference proceedingChapter

9 Citations (Scopus)


In this survey, we focus on problems of decision making under uncertainty. First, we clarify the meaning of the word “uncertainty” and we describe the general structure of problems that fall into this class. Second, we provide a list of problems from the Constraint Programming, Artificial Intelligence, and Operations Research literatures in which uncertainty plays a role. Third, we survey existing modeling frameworks that provide facilities for handling uncertainty. A number of general purpose and specialized hybrid solution methods are surveyed, which deal with the problems in the list provided. These approaches are categorized into three main classes: stochastic reasoning-based, reformulation-based, and sample-based. Finally, we provide a classification for other related approaches and frameworks in the literature
Original languageEnglish
Title of host publicationHybrid optimization: the 10 years of CPAIOR
EditorsM. Milano, P. van Hentenryck
Place of PublicationNew York
Publication statusPublished - 2010

Publication series

NameSpringer optimization and its apllications

Fingerprint Dive into the research topics of 'A survey on CP-AI-OR hybrids for decision making under uncertainty'. Together they form a unique fingerprint.

  • Cite this

    Hnich, B., Rossi, R., Tarim, S. A., & Prestwich, S. (2010). A survey on CP-AI-OR hybrids for decision making under uncertainty. In M. Milano, & P. van Hentenryck (Eds.), Hybrid optimization: the 10 years of CPAIOR (pp. 227-270). (Springer optimization and its apllications; No. 45).. https://doi.org/10.1007/978-1-4419-1644-0_7