• DocumentCode
    3154752
  • Title

    Memetic Algorithm for operating room admissions

  • Author

    Souki, Mejdi ; Ben Youssef, S. ; Rebai, Abdelwaheb

  • Author_Institution
    Fac. de Sci. Economique et de Gestion, Univ. de Sfax, Sfax, Tunisia
  • fYear
    2009
  • fDate
    6-9 July 2009
  • Firstpage
    519
  • Lastpage
    524
  • Abstract
    In this paper, we propose an efficient Memetic Algorithm (MA) which combines the Genetic Algorithm (GA) and Variable Neighbourhood Decent (VND) to solve the operating room admissions. Operating room admissions consists in assigning from the waiting list the interventions on the patients in the appropriate specific time block taking into account the availability of hospital beds and the blocks. In a view to minimizing the weighted number of used blocks and the penalizing function of the violation of the respect of deadline of intervention on the patient, a formal description by a mixed integer programming and an effective memetic algorithm to the investigate problem are proposed. The proposed memetic algorithm is compared against with two other meta-heuristics GA and VNS. Finally, computational experiment shows that the proposed memetic algorithm is very effective to others compared meta-heuristics.
  • Keywords
    genetic algorithms; hospitals; integer programming; genetic algorithm; hospital beds availability; memetic algorithm; mixed integer programming; operating room admissions; variable neighbourhood decent; violation penalizing function; Ambulatory surgery; Business; Capacity planning; Genetic algorithms; Hospitals; Linear programming; Mathematical programming; Resource management; Scheduling; Time measurement; Operating rooms; memetic algorithm; variable neighborhood decent; variable neighbourhood search;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computers & Industrial Engineering, 2009. CIE 2009. International Conference on
  • Conference_Location
    Troyes
  • Print_ISBN
    978-1-4244-4135-8
  • Electronic_ISBN
    978-1-4244-4136-5
  • Type

    conf

  • DOI
    10.1109/ICCIE.2009.5223833
  • Filename
    5223833