Author
Listed:
- Andrea Ferrari
- Chiara Campanale
- Antonio Carlin
- Giulio Mangano
Abstract
In response to the dynamic demands of modern e-commerce and supply chains, this paper addresses the critical need for adaptability and efficiency through the implementation of automated storage and retrieval systems. By using an optimisation-embedded simulation methodology, the proposed study focuses on a multi-level shuttle system designed to overcome the inherent limitations of traditional storage systems. A comprehensive discrete event simulation model is developed to evaluate the performance of the multi-level shuttle system. This model includes calculations of travel time and energy consumption, taking also into account stochastic handling times associated with repetitive tasks. In addition, a dynamic programming algorithm is integrated in the simulation model to optimise the sequencing of storage and retrieval missions performed by the handling machine. The study systematically investigates various design and operational parameters, including warehouse configurations and capacity, simultaneous handling of multiple unit loads, and the dimensions of the optimisation sessions. For all configurations tested, the research demonstrates operational advantages in the simultaneous handling of two unit loads. Theoretical contributions extend the current state of simulation models for automated warehousing systems. For practitioners, the study provides empirical insights to support decision making in the configuration of automated warehouses.
Suggested Citation
Andrea Ferrari & Chiara Campanale & Antonio Carlin & Giulio Mangano, 2025.
"Performance assessment of a multi-level shuttle system: an optimisation-embedded simulation study on time and energy consumption,"
Journal of Simulation, Taylor & Francis Journals, vol. 19(4), pages 411-426, July.
Handle:
RePEc:taf:tjsmxx:v:19:y:2025:i:4:p:411-426
DOI: 10.1080/17477778.2024.2404215
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