A case-based reasoning approach to fast optimization of travel routes for large-scale AS/RSs

Jaeseok Huh (), Moon-jung Chae (), Jonghun Park () and Kwanho Kim ()
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Jaeseok Huh: Seoul National University
Moon-jung Chae: Seoul National University
Jonghun Park: Seoul National University
Kwanho Kim: Incheon National University

Journal of Intelligent Manufacturing, 2019, vol. 30, issue 4, No 16, 1765-1778

Abstract: Abstract Due to the increasing volume of stocks in the recent production and logistics environments, the scale of automated storage and retrieval systems (AS/RSs) is becoming significantly large. To optimize travel routes for such large-scale AS/RSs, an excessive computation complexity is unavoidable when the existing metaheuristics are applied due to their exhaustive nature to search for better travel routes. In this paper, we propose a method that aims to quickly optimize travel routes by using case-based reasoning. Specifically, in the casebase construction phase, the proposed method constructs a large number of cases each of which consists of the optimized travel route for a particular setting. In the reasoning phase, the travel routes in the cases are then repaired to determine the optimal travel route for the current setting. The experiment results show that the proposed method successfully yields optimized travel routes in a short time compared to the conventional methods for the real-world scale problems.

Keywords: Fast optimization; Case-based reasoning; Automated storage and retrieval system; Travel route optimization (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10845-017-1349-8

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