A sorting based efficient heuristic for pooled repair shop designs

Hasan Hüseyin Turan, Andrei Sleptchenko, Shaligram Pokharel, Tarek Y. ElMekkawy

    Research output: Contribution to journalArticlepeer-review

    9 Scopus citations


    In this paper, we address the assignment problem of skills to servers (e.g., repairmen) in a multi-server repair shop of a spare parts supply system. This type of assignment problems tends to be hard in general, due to the lack of analytical queuing models with skill-based item-server assignments. In this paper, we propose a joint skill-server assignment and inventory optimization heuristic based on “pooled” repair shop designs. The heuristic decomposes the repair shop problem into sub-systems based on some attributes of repairable items. Each subsystem is responsible for its group of repairable items with full cross-training of the subsystem servers. The pooled designs reduce the complexity of the problem and enable the use of queue-theoretical approximations to optimize the inventory and repair shop capacity. The conducted numerical experiments show that the pooled skill-server assignments optimized by the proposed heuristic can reduce the total costs by 4% when compared to the skill-server assignments obtained by Genetic Algorithm and Simulated Annealing based methods. Furthermore, in terms of cost and computation speed, the proposed heuristic shows better results than a Simulation-Optimization based skill-server assignment heuristic, which considers all possible assignments.

    Original languageBritish English
    Article number104887
    JournalComputers and Operations Research
    StatePublished - May 2020


    • Heuristic
    • Maintenance
    • Pooling
    • Queuing
    • Repair Shop


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