Title:
Simulation-based optimization for driving innovation in manual order picking for a wholesale company
Authors:
- Pasquale Legato
- Rina Mary Mazza
Published in:
(2024). ECMS 2024, 38th Proceedings
Edited by: Daniel Grzonka, Natalia Rylko, Grazyna Suchacka, Vladimir Mityushev, European Council for Modelling and Simulation.
DOI: http://doi.org/10.7148/2024
ISSN: 2522-2422 (ONLINE)
ISSN: 2522-2414 (PRINT)
ISSN: 2522-2430 (CD-ROM)
ISBN: 978-3-937436-84-5
ISBN: 978-3-937436-83-8 (CD) Communications of the ECMS Volume 38, Issue 1, June 2024, Cracow, Poland June 4th – June 7th, 2024
DOI:
https://doi.org/10.7148/2024-0452
Citation format:
Pasquale legato, Rina mary mazza (2024). Simulation-Based Optimization for Driving Innovation in Manual Order Picking for a Wholesale Company, ECMS 2024, Proceedings Edited by: Daniel Grzonka, Natalia Rylko, Grazyna Suchacka, Vladimir Mityushev, European Council for Modelling and Simulation. doi:10.7148/2024-0452
Abstract:
This paper considers
organization and practice innovation in a typical warehousing system which acts
as a distribution site for groceries and miscellaneous to final retailers. The need of integrating
tactical decisions regarding storage positions in a rack-based system with
operational decisions for retrieving palletized items, under an S-shape policy,
calls for a simulation-based optimization approach. The unavoidable stochastic
features in order arrivals and composition, coupled with the natural
uncertainty related to the human operated order-picking process under
interferences and queueing, suggests resorting to a detailed discrete-event
simulation. We propose a system-generating algorithm to integrate the
combinatorial tactical choices for storage positions. The search process for
the best storage configurations is the core of our simulation optimization
framework in conjunction with an effective ranking and selection procedure.
Numerical results on scenario comparison and possible improvements in
productivity for a specific order-picking process are presented, using data and
rules from a real wholesale company.
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