Scheduling automated guided vehicles in very narrow aisle warehouses

Lukas Polten and Simon Emde

Omega, 2021, vol. 99, issue C

Abstract: In this paper, we study the scheduling of storage and retrieval of unit loads from very narrow aisles using automated guided vehicles (AGVs). As AGVs cannot pass each other in the aisles, sequencing the aisle access is essential. We propose two access policies, present multiple complexity results and formulate MIP models. We then present a large neighborhood search that produces solutions within less than 2.5% of the optimum solution on average in a short amount of time for instances with hundreds of jobs. We use our heuristic to derive insights into the best access policy, number of AGVs, as well as the optimal layout of very narrow aisle warehouses.

Keywords: Large neighborhood search; Automated guided vehicles; Very narrow aisles; Order picking; Warehousing (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0305048318304729
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:jomega:v:99:y:2021:i:c:s0305048318304729

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

DOI: 10.1016/j.omega.2020.102204

Access Statistics for this article

Omega is currently edited by B. Lev

More articles in Omega from Elsevier
Bibliographic data for series maintained by Catherine Liu ().