1965. Optimizing a human-centric order picking system via simulation
Invited abstract in session TD-54: Stochastic models in service operations, stream Stochastic modelling.
Tuesday, 14:30-16:00Room: Liberty 1.08
Authors (first author is the speaker)
| 1. | Rina Mary Mazza
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| DIMES, University of Calabria | |
| 2. | Francesca Guerriero
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| D.I.M.E.G.: Mechanical, Energy and Management Engineering, University of Calabria | |
| 3. | Pasquale Legato
|
| DIMES, University of Calabria |
Abstract
Order picking is deemed the most costly and labour-intensive process in a distribution warehouse and the backbone of successfully fulfilling client orders. Whether it be a manual, automated or robot-collaborative system, mastering the order picking process means improving the overall supply chain and business results. In the recent literature and in compliance with the Industry 5.0 paradigm, speeding up order process and keeping it accurate has been coupled with worker well-being. Both planning activities and operational policies are being designed to address this matter. Along this line of work, we present a mathematical programming model to optimize the slot location assignment in a real-world manually-operated and rack-based facility with respect to both economic and workforce wellness criteria. We then solve this model with an iterated local search inspired metaheuristic and validate the corresponding solution, in a stochastic and dynamic environment, via discrete-event simulation. The simulation stage of the proposed approach allows accounting for additional well-being amplifiers during order picking, such as proper queueing policies and list assignment in proximity of the end of a shift or day. To finish, we detail on our current experience and discuss preliminary numerical results.
Keywords
- Warehouse Design, Planning, and Control
- Simulation
- Metaheuristics
Status: accepted
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