• 한국국방경영분석학회지
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• 제6권1호
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• pp.33-50
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• 1980

• 한국국방경영분석학회지
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• 제12권2호
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• pp.82-99
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• 1986

• 한국경영과학회지
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• 제39권2호
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• pp.111-130
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• 2014

For the key factors determining victory of combat, many works have been focusing on qualitative analyses in the past. As military training paradigm changes along with technology developments, demands for scientific analysis to prepare future military strength increase regarding military training results, and big data analysis has opened such possibility. We analyze the data from KCTC (Korea Combat Training Center) training to investigate the factors affected victory in offensive operations. In this context, we develop a way to measure the victory and the factors related to it from existing studies and military doctrines. We first identify Independent variables that affect offensive operations through variable selection and propose a mathematical model to explain combat victory by performing multiple regression analysis. We also verify our results with battalion-level live training data as well as previous studies on victory factors in the military doctrines.

• 한국국방경영분석학회지
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• 제5권1호
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• pp.27-34
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• 1979

• 대한산업공학회지
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• 제41권1호
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• pp.79-85
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• 2015

Modeling and simulation has widely been used in the weapon systems acquisition, the military training, and the warfighting experimentation. A study of the warfighting experimentation had been relatively scarce in comparison to other fields (acquisition, training). The main reasons are 1) reliability of simulation model isn't sufficient and 2) collaboration between professional groups is too difficult. To solve this problem, the application framework of warfighting experimentation for military operations was proposed. And through the framework, the case study about sea fight was fulfilled. This framework provides connectivity between warfighting experimentation and military operations planning procedure. With improved reliability, active application of warfighting experimentation could contribute to fighting capability.

• 한국국방경영분석학회지
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• 제35권3호
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• pp.47-59
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• 2009

A hybrid Genetic Algorithm is applied to military resource allocation problem. Since military uses many resources in order to maximize its ability, optimization technique has been widely used for analysing resource allocation problem. However, most of the military resource allocation problems are too complicate to solve through the traditional operations research solution tools. Recent innovation in computer technology from the academy makes it possible to apply heuristic approach such as Genetic Algorithm(GA), Simulated Annealing(SA) and Tabu Search(TS) to combinatorial problems which were not addressed by previous operations research tools. In this study, a hybrid Genetic Algorithm which reinforces GA by applying local search algorithm is introduced in order to address military optimization problem. The computational result of hybrid Genetic Algorithm on Missile Interceptor Allocation problem demonstrates its efficiency by comparing its result with that of a simple Genetic Algorithm.

• 한국국방경영분석학회지
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• 제1권1호
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• pp.81-87
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• 1975

• 한국국방경영분석학회지
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• 제1권1호
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• pp.99-107
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• 1975

• 한국국방경영분석학회지
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• 제2권1호
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• pp.51-58
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• 1976

• 한국국방경영분석학회지
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• 제8권2호
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• pp.3-16
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• 1982

Under the assumption that the size of military expenditures is largely determined by economic potential and military requirements as well, this paper conducts an econometric analysis for the purpose of predicting Korea's military expenditures using a technique of pooling time-series data (1967-1976) and cross-section data(95 countries) on the percentage of military expenditures to GNP (Cross National Product) and economic growth rate.