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Mathematical Problems in Engineering
Volume 2015, Article ID 956757, 14 pages
Research Article

A Novel AHP-Based Benefit Evaluation Model of Military Simulation Training Systems

1Department of Management Sciences, R.O.C. Military Academy, Kaohsiung 830, Taiwan
2Department of Industrial Engineering and Management, National Chiao Tung University, Hsinchu 300, Taiwan

Received 1 July 2014; Accepted 22 December 2014

Academic Editor: Guangming Xie

Copyright © 2015 Kuei-Hu Chang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


With the constantly changing patterns of war, more technologically exquisite weapons are designed, increasing in cost and complexity. Training maneuvers with live ammunition are expensive and are prone to accidental casualties. Thus, many countries are gradually adopting simulation training systems to replace some actual exercises to reduce casualties and still maintain maximum combat readiness. However, each simulation training system has a different background with regard to time, source, function goal, and quality of environment and staff. It is also more difficult to assess the benefit of simulation training systems. Moreover, traditional benefit assessments of military simulation training systems have merely considered their efficiency, not safety, causing biased conclusions. To solve these issues, this paper integrates the analytic hierarchy process (AHP), important-performance analysis (IPA), and the 2-tuple fuzzy linguistic representation model to determine the benefits of simulation training systems. To verify the proposed approach, a numerical example of the evaluation of a training simulator system’s benefit is adopted. Compared with the traditional AHP method, the proposed method does not lose any valuable information that is provided by experts and also considers training safety. Further, these data are presented in 2-dimensional graphs for managers to further guide the decision-making process.