Spare parts stocking analysis using genetic programming

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  author =       "Bissan Ghaddar and Nizar Sakr and Yaw Asiedu",
  title =        "Spare parts stocking analysis using genetic
  journal =      "European Journal of Operational Research",
  volume =       "252",
  number =       "1",
  pages =        "136--144",
  year =         "2016",
  ISSN =         "0377-2217",
  DOI =          "doi:10.1016/j.ejor.2015.12.041",
  URL =          "",
  abstract =     "Optimal solutions to the Level of Repair Analysis
                 (LORA) and the Spare Parts Stocking (SPS) problems are
                 essential in achieving a desired system/equipment
                 operational availability. Although these two problems
                 are interdependent, they are seldom solved
                 simultaneously due to the complicating nature of the
                 relationships between spare levels and system
                 availability (or expected backorder) thus leading to
                 sub-optimal solutions for both problems. This paper
                 uses genetic programming-based symbolic regression
                 methodology to evolve simpler mathematical expressions
                 for the expected backorder equation. In addition to
                 making the SPS problem more tractable, the simpler
                 mathematical expressions make it possible for a
                 combined SPS and LORA model to be formulated and solved
                 using standard optimization techniques. Three sets of
                 spare parts stocking problems are presented to study
                 the feasibility of the proposed approach. Further, a
                 case study for the joint problem is solved which shows
                 that the proposed methodology can tackle the integrated
  keywords =     "genetic algorithms, genetic programming, Spare parts,
                 Level of Repair Analysis, Symbolic regression,

Genetic Programming entries for Bissan Ghaddar Nizar Sakr Yaw Asiedu