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A Study on the Optimal Allocation for Intelligence Assets Using MGIS and Genetic Algorithm
Author(s) -
Young-Hwa Kim,
Suhwan Kim
Publication year - 2015
Publication title -
journal of korean institute of industrial engineers
Language(s) - English
Resource type - Journals
eISSN - 2234-6457
pISSN - 1225-0988
DOI - 10.7232/jkiie.2015.41.4.396
Subject(s) - computer science , genetic algorithm , geospatial analysis , field (mathematics) , asset (computer security) , set (abstract data type) , operations research , reliability (semiconductor) , artificial intelligence , data mining , machine learning , computer security , engineering , mathematics , cartography , pure mathematics , programming language , quantum mechanics , power (physics) , geography , physics
Department of Operations Research, Korea National Defense UniversityThe literature about intelligence assets allocation focused on mainly single or partial assets such as TOD and GSR. Thus, it is limited in application to the actual environment of operating various assets. In addition, field units have generally vulnerabilities because of depending on qualitative analysis. Therefore, we need a methodology to ensure the validity and reliability of intelligence asset allocation. In this study, detection probability was generated using digital geospatial data in MGIS (Military Geographic Information System) and simulation logic of BCTP (Battle Commander Training Programs) in the R.O.K army. Then, the optimal allocation mathematical model applied concept of simultaneous integrated management, which was developed based on the partial set covering model. Also, the proposed GA (Genetic Algorithm) provided superior results compared to the mathematical model. Consequently, this study will support effectively decision making by the commander by offering the best alternatives for optimal allocation within a reasonable time.

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