Title: A genetic algorithm for the generalised sequencing problem for automated storage and retrieval systems

Authors: Eunyong Chung, H. Felix Lee

Addresses: Department of Global Business, DongHae University, DonghaeSi, KangwonDo 240-713, S. Korea. ' Industrial and Manufacturing Engineering, Southern Illinois University, Edwardsville, IL 62026-1805, USA

Abstract: With continuing need for high throughput Automated Storage and Retrieval Systems (AS/RS), many researchers have studied a problem of sequencing storage and retrieval requests processed by the Storage/Retrieval (S/R) machine to maximise the system throughput. These studies assume that each retrieval request is fixed with a predetermined bin position in the AS/RS rack. However, in reality, a retrieval request is associated with a specific product item which is available in multiple bin locations. Recently, a generalised sequencing problem has been introduced that determines both specific bin locations for the retrieval requests and sequencing with the chosen bin locations. To solve this new complex combinatorial problem, the existing solution methods rely on greedy heuristics. In this paper, we present a meta-search method based on Genetic Algorithm (GA) and report computational results in comparison with the greedy heuristics.

Keywords: automated storage and retrieval systems; AS/RS; bin locations; sequencing; system throughput; genetic algorithms; GAs; greedy heuristics.

DOI: 10.1504/IJSOI.2008.017707

International Journal of Services Operations and Informatics, 2008 Vol.3 No.1, pp.90 - 106

Published online: 27 Mar 2008 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article