Title
Simulation based particle swarm optimization of cross-training policies in spare parts supply systems
Abstract
We 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).
Year
DOI
Venue
2017
10.1109/ICACI.2017.7974486
2017 Ninth International Conference on Advanced Computational Intelligence (ICACI)
Keywords
Field
DocType
Particle Swarm Optimization,simulation,multi-skilled server,heuristic skill Allocation,maintenance logistics
Particle swarm optimization,Heuristic,Spare part,Computer science,Server,Unavailability,Probability distribution,Linear programming,Maintenance engineering,Reliability engineering
Conference
ISBN
Citations 
PageRank 
978-1-5090-4727-7
1
0.35
References 
Authors
10
4
Name
Order
Citations
PageRank
Andrei Sleptchenko18310.64
Tarek ElMekkawy271.80
Hasan Hüseyin Turan3105.22
Shaligram Pokharel411411.78