IJME 383

Paper title: FAHP for Selecting Transport Modes of Taiwan Off-Shore Islands’ Military Logistics

Authors

Y-J Wang, and T-C Han, Department of Shipping and Transportation Management, National Penghu University of Science and Technology, Taiwan, ROC
C-C Chung, Department of Shipping and Transportation Management, National Taiwan Ocean University, Taiwan, ROC and C-L Fang, Formosa Marble Tw Company Ltd., Taiwan, ROC

Summary 

Three off-shore islands of Taiwan: Penghu, Kinmen and Matsu are critical in tactical position for Taiwan military, but lack of scarcity resource. Therefore, logistics is very important especially for the off-shore islands. Practically, most of the goods and materials are transported to the islands in the way of shipping and air transportation by Taiwan. However, the severe weather of the islands makes the transportation difficult or even to delay, which is a serious problem for the military logistics of the islands. To raise transportation performance, a proper evaluation method is necessary for military logistics to select the best transport mode based on reducing cost and emphasizing efficiency. Generally, analytic hierarchy process (AHP) may be a method in the selection of transport modes for Taiwan off-shore islands’ military logistics. However, some computation procedures in AHP are hard or complicated especially for processing numerous interviewees’ messages. To resolve the above tie, we utilize fuzzy analytic hierarchy process (FAHP) in selecting transport modes for Taiwan off-shore islands’ military logistics in this paper. After integrating interviewees’ (i.e., querying soldiers’) opinions into fuzzy pair-wise comparison matrices, FAHP, being different from AHP, simply and efficiently yields priorities of the fuzzy pair-wise comparison matrices to find the best transport mode of Taiwan off-shore islands’ military logistics.

Reference

Transactions RINA, Vol 158, Part A4, International Journal Maritime Engineering, Oct-Dec 2016 

DOI Number

DOI No: 10.3940/rina.ijme.2016.a4.383

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