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 route...

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Published inDecision Science Letters Vol. 14; no. 3; pp. 739 - 752
Main Authors Nitayaprapha, Thanasit, Pochan, Jessada, Panichakarn, Boonsub, Kulthunyahirun, Supakyada
Format Journal Article
LanguageEnglish
Published Growing Science 01.06.2025
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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.
AbstractList 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.
Author Panichakarn, Boonsub
Nitayaprapha, Thanasit
Pochan, Jessada
Kulthunyahirun, Supakyada
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