A Simulation-Based Approach for the Productivity Improvement of Automated Storage and Retrieval Systems in the Steel Industry

In automated storage and retrieval systems (AS/RS), the usage of intelligent algorithms can lead to a reduction in the makespan required to complete a series of input/output operations. This paper presents a simulation-optimisation algorithm which aims at minimising the makespan in a realistic AS/RS very frequent int the steel sector, which includes weight and quality constraints of the selected items. Our hybrid approach combines discrete-event simulation with biased-randomised heuristics, which allows us to efficiently address the complex time dependencies that arise in such dynamic scenarios and, at the same time, make smart decisions that lead to feasible and high-quality solutions in a few seconds of computing time. A series of computational experiments illustrate the potential of our approach, which outperforms an alternative one based on a traditional simulated annealing