Optimal Location Selection Algorithm of MSAP for Tactical Communication Networks

- Journal title : The Journal of Korean Institute of Communications and Information Sciences
- Volume 36, Issue 12B, 2011, pp.1736-1743
- Publisher : The Korean Institute of Communications and Information Sciences
- DOI : 10.7840/KICS.2011.36B.12.1736

Title & Authors

Optimal Location Selection Algorithm of MSAP for Tactical Communication Networks

Cho, Sang-Mok; Kang, Jung-Ho; Kim, Jae-Hyun;

Cho, Sang-Mok; Kang, Jung-Ho; Kim, Jae-Hyun;

Abstract

In Network Centric Warfare (NCW) environment, having a tactical communication network which provides high data exchange rate is very important. In the process, Korean Army developed Mobile Subscriber Access Point (MSAP) which is based on the commercial Wireless BroadBand (Wibro). MSAP is a vehicle attached base station which provide high data exchange communication environment in a given area. Thus MSAP can provide high data exchange rate and mobility to accomplish missions in the battlefield more effectively. In this paper, we propose an operational strategy of using MSAP to provide tactical communication network in the battlefield. The idea is to find the optimal location point of the MSAP in the operational area where all the troops in the operational area can be supported by the MSAP with a minimum number of MSAP. Since the current Korean Army's basic idea of using MSAP is just distribute this MSAP to each troop, so by applying our strategy we can save MSAP devices for more flexible operation. We will show our strategy's benefits through the mathematical model and the algorithm of the presented problem.

Keywords

NCW;Wibro;MSAP;Optimal location;

Language

Korean

References

1.

R. L. Radin, Omptimization in Operations Research, Pearson Education, pp. 567, 1998.

2.

M. R. Garey, D. S. Johnson, Computers and Intractability: A Guide to the Theory of NP-Completeness. Freeman, San Francisco, USA. 1979.

3.

M. Desrochers, Y. Dumas, F. Soumis, and P. Trudeau, "Column Generatino Approaches to Ariline Crew Scheduling Problems," TRISTAN Conference, Montreal, 1991.

4.

A. Capara, M. Fischetti, P. Toth, D. Vigo, P. L. Guida, "Algorithms for railway crew management," Mathematical Programming 79, pp. 125-.141. 1997.

5.

M. Fisher, P. Kedia, "Optimal solution of set covering/partitioning problems using dual heuristics," management Science 36, pp. 674- 688, 1990.

6.

V. Chvatal, "A greedy heuristic for the set-covering problem," Mathematics of Operations Research 4, pp. 233-.235. 1979.

7.

F. J. Vasko, G. R. Wilson, "An efficient heuristic for large set covering problems," Naval Research Logistics Quarterly 31, pp. 163 -171, 1984.

8.

L. Jacobs, M. Brusco, "Note: A local-search heuristic for large set-covering problems," Naval Research Logistics 42, pp. 1129-1140. 1995.

9.

J. E. Beasley, P. C. Chu, "A genetic algorithm for the set covering problem," European Journal of Operational Research 94, 392-404., 1996.

10.

U. Aickelin, "An indirect genetic algorithm for set covering problems," Journal of the Operational Research Society 53, pp. 1118- 1126, 2002.

11.

L. Lessing, I. Dumitrescu, T. Stutzle, "A comparison between ACO algorithms for the set covering problem," Lecture Notes in Computer Science 3172, pp. 1-12, 2004.

12.

F. Glover, M. Laguna, Tabu Search, Springer, pp.2-5. 1998