A route selection process using a multicriteria decision-making (MCDM) approach based on the simple additive weighting (SAW) method: Evidence from Thai fresh fruit exported to China by road transportation

This study identifies the optimal route for transporting agricultural fruits using the Simple Additive Weighting (SAW) method within a Multicriteria Decision-Making (MCDM) framework. Data was gathered through a literature review on transportation principles, route selection criteria, and truck routes, identifying eight critical factors for route selection. Transportation route data were also systematically collected, forming the basis of the proposed conceptual framework. The SAW analysis identified the highest-scoring routes for each segment: Route A1 (6.35406), Route B1 (6.38532), Route C1 (6.26248), and Route D3 (5.29061). Historical data from the past five years confirmed consistency in route selection. Comparatively, Dijkstra's Algorithm, based on single factors like distance, time, or cost, proved less effective for agricultural transportation. In contrast, the SAW method, integrating multiple factors, ensured more accurate route selection. Key influencing factors included road conditions, infrastructure or road width, and facility availability. The optimal route from Thailand to China was Route A1-B1, passing through Chanthaburi, Rayong, Chonburi, Chachoengsao, Samut Prakan, Bangkok, Pathum Thani, Ayutthaya, Ang Thong, Sing Buri, Chai Nat, Nakhon Sawan, Phichit, Phitsanulok, Uttaradit, Phrae, Lampang, Phayao, and Chiang Rai, terminating at Chiang Khong Customs Checkpoint. These findings offer practical guidance for planning and decision-making in agricultural transportation routes.

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Publication Details

Journal
Decision Science Letters
Published
2025-01-01
DOI
https://doi.org/10.5267/j.dsl.2025.3.007
Citations
1
Primary Topic
Multi-Criteria Decision Making
Type
article
Field-Weighted Citation Impact
2.11

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article

A route selection process using a multicriteria decision-making (MCDM) approach based on the simple additive weighting (SAW) method: Evidence from Thai fresh fruit exported to China by road transportation

Jessada Pochan, Boonsub Panichakarn, Thanasit Nitayaprapha, Supakyada Kulthunyahirun
1 citations
Decision Science Letters
Multi-Criteria Decision Making
2.11
article

A route selection process using a multicriteria decision-making (MCDM) approach based on the simple additive weighting (SAW) method: Evidence from Thai fresh fruit exported to China by road transportation

Jessada Pochan, Boonsub Panichakarn, Thanasit Nitayaprapha, Supakyada Kulthunyahirun
article en
1 citations

Abstract

This study identifies the optimal route for transporting agricultural fruits using the Simple Additive Weighting (SAW) method within a Multicriteria Decision-Making (MCDM) framework. Data was gathered through a literature review on transportation principles, route selection criteria, and truck routes, identifying eight critical factors for route selection. Transportation route data were also systematically collected, forming the basis of the proposed conceptual framework. The SAW analysis identified the highest-scoring routes for each segment: Route A1 (6.35406), Route B1 (6.38532), Route C1 (6.26248), and Route D3 (5.29061). Historical data from the past five years confirmed consistency in route selection. Comparatively, Dijkstra's Algorithm, based on single factors like distance, time, or cost, proved less effective for agricultural transportation. In contrast, the SAW method, integrating multiple factors, ensured more accurate route selection. Key influencing factors included road conditions, infrastructure or road width, and facility availability. The optimal route from Thailand to China was Route A1-B1, passing through Chanthaburi, Rayong, Chonburi, Chachoengsao, Samut Prakan, Bangkok, Pathum Thani, Ayutthaya, Ang Thong, Sing Buri, Chai Nat, Nakhon Sawan, Phichit, Phitsanulok, Uttaradit, Phrae, Lampang, Phayao, and Chiang Rai, terminating at Chiang Khong Customs Checkpoint. These findings offer practical guidance for planning and decision-making in agricultural transportation routes.

Decision Science LettersVol. 14(3)
Naresuan University
Openalex Percentile: Top 13%
Multi-Criteria Decision Making
2.11
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