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

Jaeseok Huh, Moon jung Chae, Jonghun Park, Kwanho Kim

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

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.

Original languageEnglish
Pages (from-to)1765-1778
Number of pages14
JournalJournal of Intelligent Manufacturing
Volume30
Issue number4
DOIs
StatePublished - 1 Apr 2019

Keywords

  • Automated storage and retrieval system
  • Case-based reasoning
  • Fast optimization
  • Travel route optimization

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