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AuthorSleptchenko, Andrei
AuthorElmekkawy, Tarek
AuthorTuran, Hasan Huseyin
AuthorPokharel, Shaligram
Available date2021-01-27T11:06:53Z
Publication Date2017
Publication Name9th International Conference on Advanced Computational Intelligence, ICACI 2017
ResourceScopus
URIhttp://dx.doi.org/10.1109/ICACI.2017.7974486
URIhttp://hdl.handle.net/10576/17473
AbstractWe study a single location supply system for repairable spare parts. The system consists of a multi-server repair shop and inventory with ready-to-use spare parts. When a failed part is received, a new (or as-good-as-new) replacement part is sent back, and the failed part is forwarded to the repairshop. In the case of unavailability of spare parts, failed requests are backordered and fulfilled when a ready-for-use part of the same type is received from the repairshop. The repair shop has several multi-skilled parallel servers (technicians) that are capable of handling certain types of spares. In this paper, we propose a Particle Swarm Optimization heuristic combined with Discrete-Event Simulation for optimizing the cross-training policy (skill assignment scheme) while minimizing the total system cost (consisting of inventory costs, backorder penalty cost, server cost and skill cost).
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc.
Subjectheuristic skill Allocation
maintenance logistics
multi-skilled server
Particle Swarm Optimization
simulation
TitleSimulation based particle swarm optimization of cross-training policies in spare parts supply systems
TypeConference Paper
Pagination60-65
dc.accessType Abstract Only


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