Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

Optimization of the Storage Location Assignment Problem Using Nested Annealing

Oxenstierna, Johan LU orcid ; van Rensburg, Louis Janse ; Stuckey, Peter J. and Krueger, Volker LU orcid (2024) 11th and 12th International Conferences on Operations Research and Enterprise Systems, ICORES 2022 and 2023 In Communications in Computer and Information Science 1985 CCIS. p.220-244
Abstract

The Storage Location Assignment Problem (SLAP) has a significant impact on the efficiency of warehouse operations. We propose a multi-phase optimizer for the SLAP, where the quality of an assignment is based on distance estimates of future-forecasted order-picking. Candidate assignments are first sampled using a Markov Chain accept/reject method. Order-picking Traveling Salesman Problems (TSPs) are then modified according to the assignments and solved. The model is graph-based and generalizes to any obstacle layout in two dimensions. We investigate whether optimization speed-ups are possible using methods such as cost approximation, rejection of samples with low approximate cost and restarts from local minima. Results demonstrate that... (More)

The Storage Location Assignment Problem (SLAP) has a significant impact on the efficiency of warehouse operations. We propose a multi-phase optimizer for the SLAP, where the quality of an assignment is based on distance estimates of future-forecasted order-picking. Candidate assignments are first sampled using a Markov Chain accept/reject method. Order-picking Traveling Salesman Problems (TSPs) are then modified according to the assignments and solved. The model is graph-based and generalizes to any obstacle layout in two dimensions. We investigate whether optimization speed-ups are possible using methods such as cost approximation, rejection of samples with low approximate cost and restarts from local minima. Results demonstrate that these methods improve performance, with total travel-cost reductions of up to 30% within 8 h of CPU-time. We share a public repository with SLAP instances and corresponding benchmark results on the generalizable TSPLIB format.

(Less)
Please use this url to cite or link to this publication:
author
; ; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Hamming distances, Nested annealing, Storage location assignment problem
host publication
Operations Research and Enterprise Systems : 11th International Conference, ICORES 2022, Virtual Event, February 3–5, 2022, and 12th International Conference, ICORES 2023, Lisbon, Portugal, February 19-21, 2023, Revised Selected Papers - 11th International Conference, ICORES 2022, Virtual Event, February 3–5, 2022, and 12th International Conference, ICORES 2023, Lisbon, Portugal, February 19-21, 2023, Revised Selected Papers
series title
Communications in Computer and Information Science
editor
Liberatore, Federico ; Wesolkowski, Slawo ; Demange, Marc and Parlier, Greg H.
volume
1985 CCIS
pages
25 pages
publisher
Springer Science and Business Media B.V.
conference name
11th and 12th International Conferences on Operations Research and Enterprise Systems, ICORES 2022 and 2023
conference location
Lisbon, Portugal
conference dates
2023-02-19 - 2023-02-21
external identifiers
  • scopus:85180554905
ISSN
1865-0937
1865-0929
ISBN
978-3-031-49662-2
978-3-031-49661-5
DOI
10.1007/978-3-031-49662-2_12
language
English
LU publication?
yes
id
86de5253-29dc-4d35-a573-58f0e5ffe172
date added to LUP
2024-02-06 15:18:50
date last changed
2025-01-29 02:30:09
@inproceedings{86de5253-29dc-4d35-a573-58f0e5ffe172,
  abstract     = {{<p>The Storage Location Assignment Problem (SLAP) has a significant impact on the efficiency of warehouse operations. We propose a multi-phase optimizer for the SLAP, where the quality of an assignment is based on distance estimates of future-forecasted order-picking. Candidate assignments are first sampled using a Markov Chain accept/reject method. Order-picking Traveling Salesman Problems (TSPs) are then modified according to the assignments and solved. The model is graph-based and generalizes to any obstacle layout in two dimensions. We investigate whether optimization speed-ups are possible using methods such as cost approximation, rejection of samples with low approximate cost and restarts from local minima. Results demonstrate that these methods improve performance, with total travel-cost reductions of up to 30% within 8 h of CPU-time. We share a public repository with SLAP instances and corresponding benchmark results on the generalizable TSPLIB format.</p>}},
  author       = {{Oxenstierna, Johan and van Rensburg, Louis Janse and Stuckey, Peter J. and Krueger, Volker}},
  booktitle    = {{Operations Research and Enterprise Systems : 11th International Conference, ICORES 2022, Virtual Event, February 3–5, 2022, and 12th International Conference, ICORES 2023, Lisbon, Portugal, February 19-21, 2023, Revised Selected Papers}},
  editor       = {{Liberatore, Federico and Wesolkowski, Slawo and Demange, Marc and Parlier, Greg H.}},
  isbn         = {{978-3-031-49662-2}},
  issn         = {{1865-0937}},
  keywords     = {{Hamming distances; Nested annealing; Storage location assignment problem}},
  language     = {{eng}},
  pages        = {{220--244}},
  publisher    = {{Springer Science and Business Media B.V.}},
  series       = {{Communications in Computer and Information Science}},
  title        = {{Optimization of the Storage Location Assignment Problem Using Nested Annealing}},
  url          = {{http://dx.doi.org/10.1007/978-3-031-49662-2_12}},
  doi          = {{10.1007/978-3-031-49662-2_12}},
  volume       = {{1985 CCIS}},
  year         = {{2024}},
}