Published September 12, 2011
| Version v1
Conference paper
Solving Problems with CP: Four Common Pitfalls to Avoid
Creators
Contributors
Others:
- Modèles Discrets pour les Systèmes Complexes (Laboratoire I3S - MDSC) ; Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S) ; Université Nice Sophia Antipolis (1965 - 2019) (UNS) ; COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS) ; COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)
- Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S) ; Université Nice Sophia Antipolis (1965 - 2019) (UNS) ; COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)
- Jimmy Ho-Man Lee
Description
Constraint Programming (CP) is a general technique for solving combinatorial optimization problems. Real world problems are quite complex and solving them requires to divide work into different parts. Mainly, there are: the abstraction of interesting and relevant sub-parts, the definition of benchmarks and design of a global model and the application of a particular search strategy. We propose to identify for each of these parts some common pitfalls and to discuss them. We will successively consider undivided model, rigid search, biased benchmarking and wrong abstraction.
Abstract
International audienceAdditional details
Identifiers
- URL
- https://hal.science/hal-01344048
- URN
- urn:oai:HAL:hal-01344048v1
Origin repository
- Origin repository
- UNICA