데이터 마이닝 기반의 군사특기 분류 방법론 연구 = A Data-Mining-based Methodology for Military Occupational Specialty Assignment

다국어 초록 (Multilingual Abstract)

In this paper, we propose a new data-mining-based methodology for military occupational specialty assignment. The proposed methodology consists of two phases, feature selection and man-power assignment. In the first phase, the k-means partitioning algorithm and the optimal variable weighting algorithm are used to determine attribute weights. We address limitations of the optimal variable weighting algorithm and suggest a quadratic programming model that can handle categorical variables and non-contributory trivial variables. In the second phase, we present an integer programming model to deal with a man-power assignment problem. In the model, constraints on demand-supply requirements and training capacity are considered. Moreover, the attribute weights obtained in the first phase for each specialty are used to measure dissimilarity. Results of a computational experiment using real-world data are provided along with some analysis.

참고문헌 (Reference)

1 Klingman, "Topological and Computational Aspects of Preemptive Multicriteria Military Personnel Assignment Problem" 1362-1375, 1984

2 MacQueen, "Some Methods for Classification and Analysis of Multivariate Observations Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability University of California Press" 281-297, 1967

3 "Optimum Manpower Models for a Production System with Varying Production Rates European Journal of Operational Research" 447-454, 1986

4 Baumgarten, B, "Optimization of United States Marine Corps Officer Career Path Selection" Naval Postgraduate Schoo 2000

5 Makarenkov, V, "Optimal Variable Weighting for Ultrametric and Additive Trees and K-means Partitioning: Method and Software" 18 : 245-271, 2001

6 van Dam, "On the Optimal Allocation of Crewmen Aboard a Warship" 503-517, 1981

7 "Manpower Planning with Uncertain Requirement" gri (gri): 177-189, 1976

8 "Interactive Multiple Objective Programming Subject to Flexible Constraints European Journal of Operational Research" 342-349, 1987

9 Liang, "Improving the Utilization of Training Resources through Optimal Personnel Assignment in the U European Journal of Operational Research" 183-1901988

10 Talbot, "Improving the Equality of Workload Assignments in Assembly lines International Journal of Productions Research" 619-633, 1991

11 Huang, Z, "Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values" 2 : 283-304, 1998

12 "Decision Support for Massive Personnel Assignment" 355-363, 1989

13 "Decision Support System - An Application in Strategic Manpower Planning of Airline Pilots European Journal of Operational Research" 368-381, 1991

14 Anderberg, "Cluster analysis for applications" Academic Press 1973

15 Bobrowski, "An Evaluation of Labor Assignment Rules When Workers Are not Perfectly Interchangeable Journal of Operations Management" 257-268, 1993

16 I, "An Efficient Heuristic Method for the Simple Assembly Line Balancing Problem International Journal of Production Research" 149-166, 1986

17 Sweetser, A, "An Analysis of Personnel Distribution Options for the Chief of Staff, Army," 34 (34): 12-15, 2001

18 Naracimhan, R, "An Algorithm for Single Shift Scheduling of Hierarchical Workforce" 96 (96): 113-121, 1996

19 Fayyad, M, "Advances in Knowledge Discovery and Data Mining" MIT Press 1996

20 Liang, "A Systems Approach to Integrate Manpower Planning and Operation" socio-eco (socio-eco): 371-377, 1984

21 Burns, "A Modular Approach to Optimal Multiple-Shift Manpower Scheduling" 100-110, 1987

22 Liang, "A Large-Scale Personnel Assignment Model for the Navy" 234-249, 1987

23 정지원, "A Genetic Algorithm for Clustering in Data Mining" 대한산업공학회/한국경영과학회 306-309, 2000

24 "A Branch and Bound Approach for Machine Load Balancing in Flexible Manufacturing System" 1316-1341, 1986