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Memory and feasibility indicators in GRASP for Multi-Skill Project Scheduling with Partial Preemption

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  • Additional Information
    • Contributors:
      Commissariat à l'énergie atomique et aux énergies alternatives (CEA); Équipe Recherche Opérationnelle, Optimisation Combinatoire et Contraintes (LAAS-ROC); Laboratoire d'analyse et d'architecture des systèmes (LAAS); Université Toulouse Capitole (UT Capitole); Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse); Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J); Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3); Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP); Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole); Université de Toulouse (UT); University of Hagen Allemagne; ANR-19-P3IA-0004,ANITI,Artificial and Natural Intelligence Toulouse Institute(2019)
    • Publication Information:
      HAL CCSD
    • Publication Date:
      2019
    • Collection:
      Université Toulouse 2 - Jean Jaurès: HAL
    • Subject Terms:
      Carthagène des Indes; Colombia
    • Abstract:
      International audience ; This paper describes a GRASP algorithm aiming to solve a new scheduling problem known as the Multi-Skill Project Scheduling Problem with Partial Preemption, in which not all resources are released during preemption periods. We use a self-adaptive strategy for fixing the cardinality of the restricted candidate list in the greedy phase of the GRASP. We also propose an adaptive evaluation function that includes memory-based intensification, exploiting the characteristics of the best solutions, and a feasibility element for increasing the number of feasible solutions visited. Numerical experiments show the interest of the proposed approach.
    • Relation:
      hal-02264213; https://hal.science/hal-02264213; https://hal.science/hal-02264213/document; https://hal.science/hal-02264213/file/MIC2019.pdf
    • Online Access:
      https://hal.science/hal-02264213
      https://hal.science/hal-02264213/document
      https://hal.science/hal-02264213/file/MIC2019.pdf
    • Rights:
      info:eu-repo/semantics/OpenAccess
    • Accession Number:
      edsbas.1E56C6A6