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(Confpaper: IEEETrans, accepted) Simulation Based Particle Swarm Optimization of Cross-Training Policies in Spare Parts Supply Systems
  • +2
  • Andrei SleptchenkoOrcid,
  • Tarek Elmekkawy,
  • Hasan Hüseyin Turan,
  • Shaligram,
  • Maryam Al-Khatib
Andrei Sleptchenko
Orcid
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Tarek Elmekkawy
Qatar University
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Hasan Hüseyin Turan
Qatar University
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Shaligram
Qatar University
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Maryam Al-Khatib
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Abstract

We study a single location supply system for repairable spare parts. The system consists of a multi-server repairshop and an inventory with ready-to-use spare parts. When a failed part is received, a new (or as-good-as-new) replacement (if available in the inventory) is sent back and the failed part is sent to the repair shop. In case of unavailability, failed requests are backordered and fulfilled when a ready-for-use part of same type is received from the repairshop. The repair shop has several multi-skilled parallel servers (technicians) that are capable to handle 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).