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Handling fuzzy temporal constraints in a planning environment

Author

Listed:
  • Marc Asunción
  • Luis Castillo
  • Juan Fernández-Olivares
  • Oscar García-Pérez
  • Antonio González
  • Francisco Palao

Abstract

An interleaved integration of the planning and scheduling process is presented with the idea of including soft temporal constraints in a partial order planner that is being used as the core module of an intelligent decision support system for the design forest fire fighting plans. These soft temporal constraints have been defined through fuzzy sets. This representation allows us a flexible representation and handling of temporal information. The scheduler model consists of a fuzzy temporal constraints network whose main goal is the consistency checking of the network associated to each partial order plan. Moreover, we present a model of estimating this consistency, and show the monitoring and rescheduling capabilities of the system. The resulting approach is able to tackle problems with ill defined knowledge, to obtain plans that are approximately consistent and to adapt the execution of plans to unexpected delays. Copyright Springer Science+Business Media, LLC 2007

Suggested Citation

  • Marc Asunción & Luis Castillo & Juan Fernández-Olivares & Oscar García-Pérez & Antonio González & Francisco Palao, 2007. "Handling fuzzy temporal constraints in a planning environment," Annals of Operations Research, Springer, vol. 155(1), pages 391-415, November.
    • Handle: RePEc:spr:annopr:v:155:y:2007:i:1:p:391-415:10.1007/s10479-007-0207-z
    DOI: 10.1007/s10479-007-0207-z
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    References listed on IDEAS

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    1. Dubois, Didier & Fargier, Helene & Fortemps, Philippe, 2003. "Fuzzy scheduling: Modelling flexible constraints vs. coping with incomplete knowledge," European Journal of Operational Research, Elsevier, vol. 147(2), pages 231-252, June.
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    Cited by:

    1. Sanja Petrovic & Greet Berghe, 2012. "A comparison of two approaches to nurse rostering problems," Annals of Operations Research, Springer, vol. 194(1), pages 365-384, April.
    2. Sujeet Kumar Singh & Shiv Prasad Yadav, 2018. "Intuitionistic fuzzy multi-objective linear programming problem with various membership functions," Annals of Operations Research, Springer, vol. 269(1), pages 693-707, October.
    3. Sujeet Kumar Singh & Shiv Prasad Yadav, 2016. "A new approach for solving intuitionistic fuzzy transportation problem of type-2," Annals of Operations Research, Springer, vol. 243(1), pages 349-363, August.

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