A Genetic Algorithm Approach for Controlling Mobile Rack Automated Storage and Retrieval System

In this study, we address the sequencing problem of storage and retrieval operations in a Mobile Rack Automated Storage and Retrieval System (MR-AS/RS). This problem is particularly relevant to AS/RS configurations equipped with a multi-shuttle crane, where the coordination and optimization of operations directly affect system performance. The goal is to create and test effective sequencing strategies that cut down on operation time while increasing the overall system throughput. To tackle this challenge, this paper proposes the use of a specially tailored Genetic Algorithm (GA) to optimize the sequencing of storage and retrieval tasks in MR-AS/RSs. The developed GA aims to minimize the total travel time of both single- and multi-shuttle Storage/Retrieval (S/R) machines. Its performance is compared with classical heuristics and analytical models from the literature, which were originally designed to optimize similar AS/RSs. These analytical models also serve as a theoretical basis for assessing the effectiveness of the proposed control approach. A comprehensive simulation study was conducted under various system configurations, considering changes in the number of aisles, shape factors as well as item diversity. Additionally, a sensitivity analysis of the GA parameters was performed to identify the optimal settings and validate the robustness and efficiency of the proposed GA in solving the sequencing problem for MR-AS/RSs.