Performance Analysis of a Class-Based Robotic Compact Storage and Retrieval System

dc.contributor.author Tutam, M.
dc.contributor.author Liu, J.
dc.contributor.author White, J.A.
dc.date.accessioned 2026-03-26T15:02:12Z
dc.date.available 2026-03-26T15:02:12Z
dc.date.issued 2023
dc.description UCF en_US
dc.description.abstract Warehouses are often characterized by low cube utilization, which becomes an issue with land scarcity and increasing land prices. Robotic Compact Storage and Retrieval Systems (RCS/RS) have been developed to increase space utilization. They do not require traditional picking- and cross-aisles. In such a system, a grid-based storage space contains bins stacked on each other. Moreover, robots operate on the roof of the system to lift or lower bins in stacks while transporting them between storage locations and ports. The question is what the dimensions of an RCS/RS should be because operation times for the system differ based on the speed of robots, as well as the x-, y- and z-dimensions and the number of bins. To minimize the expected operation time of a robot to complete storage/retrieval operations, we embed a discrete formulation of the generalized assignment problem in an enumeration over the z-direction to determine the optimum allocation of bins to locations in a three-dimensional class-based storage space and the best dimensions of an RCS/RS with the proposed algorithm in a reasonable time frame. We consider three classes of bins based on different skewness values for activity levels. Our optimization model can be used to design a new RCS/RS or analyze an existing RCS/RS based on its current system parameters. © IISE and Expo 2023.All rights reserved. en_US
dc.identifier.doi 10.21872/2023IISE_3326
dc.identifier.isbn 9781713877851
dc.identifier.scopus 2-s2.0-85174953457
dc.identifier.uri https://doi.org/10.21872/2023IISE_3326
dc.identifier.uri https://hdl.handle.net/20.500.14901/3558
dc.language.iso en en_US
dc.publisher Institute of Industrial and Systems Engineers, IISE en_US
dc.relation.ispartof -- IISE Annual Conference and Expo 2023 -- 2023-05-21 through 2023-05-23 -- New Orleans -- 192872 en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.subject Class-Based Storage en_US
dc.subject Expected Operation Time en_US
dc.subject Goods-to-Person System en_US
dc.subject Performance Analysis en_US
dc.subject Robotic Compact S/Rs Technology en_US
dc.title Performance Analysis of a Class-Based Robotic Compact Storage and Retrieval System en_US
dc.type Conference Object en_US
dspace.entity.type Publication
gdc.author.scopusid 57189443629
gdc.author.scopusid 57216460077
gdc.author.scopusid 57214453843
gdc.description.department Erzurum Technical University en_US
gdc.description.departmenttemp [Tutam] Mahmut, Department of Industrial Engineering, Erzurum Technical University, Erzurum, Erzurum, Turkey; [Liu] Jingming, School of Economics and Management, Hebei University of Technology, Tianjin, China; [White] John A., Department of Industrial Engineering, College of Engineering, Fayetteville, AR, United States en_US
gdc.description.publicationcategory Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality N/A
gdc.description.wosquality N/A
gdc.virtual.author Tutam, Mahmut
relation.isAuthorOfPublication eccb155b-1299-438e-b254-b42db6482b8d
relation.isAuthorOfPublication.latestForDiscovery eccb155b-1299-438e-b254-b42db6482b8d

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