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Decision Support System for Determining Strategic Warehouse Locations Using a Combination of the WENSLO Weighting and RAWEC Method

JUTI: Jurnal Ilmiah Teknologi Informasi · Vol. 24 No. 1 (2026) · pp. 165–184

DOI
10.12962/j24068535.v24i1.a1456
ISSN
2406-8535, 1412-6389
Published
2026-01-15
Publisher
Institut Teknologi Sepuluh Nopember
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Determining the location of a strategic warehouse is a crucial decision in supply chain management as it directly affects distribution efficiency, logistics costs, and service levels. This problem is multi-criteria and complex, requiring an approach that can accommodate differences in the importance of criteria as well as variations in performance among alternatives objectively. This study aims to develop a Decision Support System to determine a strategic warehouse location by combining the Weights by Envelope and Slope (WENSLO) weighting method and the Ranking of Alternatives with Weights of Criterion (RAWEC) ranking method. The WENSLO method is used to generate criteria weights based on the nonlinear strength of each criterion, while the RAWEC method is applied to calculate the final values and determine the ranking of warehouse location alternatives. A case study was conducted on eleven alternative locations with the main criteria including location cost, accessibility, safety, distribution travel time, and proximity to suppliers. The study results showed that Location TR obtained the highest final score of 0.9673 and was designated as the top priority warehouse location, followed by Location RD with a score of 0.6235 and Location HO with a score of 0.338, while Location QC had the lowest score of −0.975. These findings demonstrate that the combination of the WENSLO and RAWEC methods can produce rankings that are objective, consistent, and easy to interpret, making them a reliable decision-support tool for determining strategic warehouse locations and potentially applicable to other logistics and distribution problems.

Collaboration network of the authors

5 authors · 10 co-authorship links · 7 across different organisations

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  • Universitas Teknokrat Indonesia
  • Zhejiang Technical Institute of Economics
  • Universitas Bina Sarana Informatika
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://juti.if.its.ac.id/index.php/juti/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc)
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	<dc:title xml:lang="en">Decision Support System for Determining Strategic Warehouse Locations Using a Combination of the WENSLO Weighting and RAWEC Method</dc:title>
	<dc:creator xml:lang="en">Wang, Junhai</dc:creator>
	<dc:creator xml:lang="en">Setiawansyah, Setiawansyah</dc:creator>
	<dc:creator xml:lang="en">Ardiansah, Temi </dc:creator>
	<dc:creator xml:lang="en">Ulum, Faruk</dc:creator>
	<dc:creator xml:lang="en">Sumanto, Sumanto</dc:creator>
	<dc:description xml:lang="en">Determining the location of a strategic warehouse is a crucial decision in supply chain management as it directly affects distribution efficiency, logistics costs, and service levels. This problem is multi-criteria and complex, requiring an approach that can accommodate differences in the importance of criteria as well as variations in performance among alternatives objectively. This study aims to develop a Decision Support System to determine a strategic warehouse location by combining the Weights by Envelope and Slope (WENSLO) weighting method and the Ranking of Alternatives with Weights of Criterion (RAWEC) ranking method. The WENSLO method is used to generate criteria weights based on the nonlinear strength of each criterion, while the RAWEC method is applied to calculate the final values and determine the ranking of warehouse location alternatives. A case study was conducted on eleven alternative locations with the main criteria including location cost, accessibility, safety, distribution travel time, and proximity to suppliers. The study results showed that Location TR obtained the highest final score of 0.9673 and was designated as the top priority warehouse location, followed by Location RD with a score of 0.6235 and Location HO with a score of 0.338, while Location QC had the lowest score of −0.975. These findings demonstrate that the combination of the WENSLO and RAWEC methods can produce rankings that are objective, consistent, and easy to interpret, making them a reliable decision-support tool for determining strategic warehouse locations and potentially applicable to other logistics and distribution problems.</dc:description>
	<dc:publisher xml:lang="en">Institut Teknologi Sepuluh Nopember</dc:publisher>
	<dc:date>2026-01-15</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:type xml:lang="en">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://juti.if.its.ac.id/index.php/juti/article/view/1456</dc:identifier>
	<dc:identifier>10.12962/j24068535.v24i1.a1456</dc:identifier>
	<dc:source xml:lang="en">JUTI: Jurnal Ilmiah Teknologi Informasi; Vol. 24, No. 1, January 2026; 165-184</dc:source>
	<dc:source>2406-8535</dc:source>
	<dc:source>1412-6389</dc:source>
	<dc:source>10.12962/j24068535.v24i1</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://juti.if.its.ac.id/index.php/juti/article/view/1456/582</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2026 Junhai Wang, Setiawansyah Setiawansyah, Temi  Ardiansah, Faruk Ulum, Sumanto Sumanto</dc:rights>
	<dc:rights xml:lang="en">https://creativecommons.org/licenses/by-sa/4.0</dc:rights>
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