# Simulation-Based Performance Analysis for a Novel AVS/RS Technology with Movable Lifts
## 2 Literature Review on AVS/RS
[16] proposed a parallel processing policy for autonomous vehicle storage and retrieval systems (SBS/RS), where an arrival transaction can request both the lift (elevator) and the vehicle (shuttle carrier) at the same time. A fork-join queueing network is formulated in which an arrival transaction is divided into a horizontal movement task served by the vehicle and a vertical movement task served by the elevator. The authors use a simulation model to validate the analytical models. Introducing a multi-elevator tier-captive shuttle-based storage and retrieval system (SBS/RS), [PERSON] et al. [17] developed an efficient simulation model that can be automatically redesigned for different storage rack configurations. The benefit of their model is to test a large number of rack alternatives in order to efficiently determine the optimal solution. By considering discrete-time open queueing network approach, [PERSON] et al. [18] proposed a method for performance evaluation of autonomous vehicle storage and retrieval systems (AVS/RSs) with single aisle tier-captive vehicles. They compare the efficiency of the model with a discrete-event simulation. In a later study, [PERSON] [19] investigated aisle-changing shuttle carriers in AVS/RSs. The author proposes analytical travel time models for aisle-changing shuttle carriers, which can travel in both horizontal and cross-aisle directions. The expressions for the travel times of single and double commands are determined under the assumption of uniformly distributed storage locations and the theory of probability. A simulation model is developed to benchmark the proposed analytical models. Very recent papers on SBS/RS were completed by [PERSON] [20]. [PERSON] et al. [1, 2, 21] proposed a tool for calculating critical performance measures of various shuttle-based storage and retrieval system (SBS/RS) designs. The proposed methodology can also be used for any system with a linear, discrete travel pattern with stop points of equal distance. Utilizing the proposed tool, the performance of SBS/RS systems can be immediately evaluated by changing the input design parameters of SBS/RS. In a later study, [PERSON] and [PERSON] [22] presented a queuing network-based tool estimating several performance metrics from a pre-defined SBS/RS design. The developed tool can be downloaded from a website for free. Besides those, to show the effectiveness of class-based storage policy, [PERSON] et al. [3] studied SBS/RS warehouse under several storage policies. Recently, [PERSON] et al. [23, 24] investigated two SBS/RS configurations (e.g., tier-captive shuttles with tier-to-tier shuttles). The authors proposed an alternative SBS/RS design with tier-to-tier shuttles, where the shuttles can travel between tiers by using a separate lifting mechanism dedicated to them. The proposed results suggest that a newly proposed tier-to-tier SBS/RS design can provide a better configuration in terms of total investment cost and throughput rate. The existing works mostly focus on design and modelling approaches for AVS/RS and SBS/RS. For instance, simulation modelling approach is one of the most powerful tools utilized for modelling of such complex systems. By that approach, several different designs could be tried for systems that could be hard to model analytically. Compared to the existing literature on AVS/RS works [5, 8, 10, 11, 12, 18, 19], the proposed research considers a novel AVS/RS technology design with MLs. These aisle-captive lifts are, only while not loaded, able to travel along the warehouse aisle to position themselves at the target column location. Further, they can, only when they are at the standstill, lift up the systems' autonomous vehicles to the target tier and lower them down to the aisle floor. To the best of our knowledge, this is the first study presenting that novel AVS/RS technology design with movable lifts, ML, and analyzing the efficiency of the proposed system with simulation under different operational aspects.