Spare parts stocking analysis using genetic programming
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- @Article{Ghaddar:2016:EJOR,
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author = "Bissan Ghaddar and Nizar Sakr and Yaw Asiedu",
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title = "Spare parts stocking analysis using genetic
programming",
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journal = "European Journal of Operational Research",
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volume = "252",
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number = "1",
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pages = "136--144",
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year = "2016",
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ISSN = "0377-2217",
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DOI = "doi:10.1016/j.ejor.2015.12.041",
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URL = "http://www.sciencedirect.com/science/article/pii/S0377221715011807",
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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
problem.",
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keywords = "genetic algorithms, genetic programming, Spare parts,
Level of Repair Analysis, Symbolic regression,
Optimization",
- }
Genetic Programming entries for
Bissan Ghaddar
Nizar Sakr
Yaw Asiedu
Citations