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http://dx.doi.org/10.5391/JKIIS.2012.22.5.540

A Study of population Initialization Method to improve a Genetic Algorithm on the Weapon Target Allocation problem  

Hong, Sung-Sam (가천대학교 전자계산학과)
Han, Myung-Mook (가천대학교 전자계산학과)
Choi, Hyuk-Jin (국방과학연구소)
Mun, Chang-Min (국방과학연구소)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.22, no.5, 2012 , pp. 540-548 More about this Journal
Abstract
The Weapon Target Allocation(WTA) problem is the NP-Complete problem. The WTA problem is that the threatful air targets are assigned by weapon of allies for killing the targets. A good solution of NP-complete problem is heuristic algorithms. Genetic algorithms are commonly used heuristic for global optimization, and it is good solution on the diverse problem domain. But there has been very little research done on the generation of their initial population. The initialization of population is one of the GA step, and it decide to initial value of individuals. In this paper, we propose to the population initialization method to improve a Genetic Algorithm. When it initializes population, the proposed algorithm reflects the characteristics of the WTA problem domain, and inherits the dominant gene. In addition, the search space widely spread in the problem space to find efficiently the good quality solution. In this paper, the proposed algorithm to verify performance examine that an analysis of various properties and the experimental results by analyzing the performance compare to other algorithms. The proposed algorithm compared to the other initialization methods and a general genetic algorithm. As a result, the proposed algorithm showed better performance in WTA problem than the other algorithms. In particular, the proposed algorithm is a good way to apply to the variety of situation WTA problem domain, because the proposed algorithm can be applied flexibly to WTA problem by the adjustment of RMI.
Keywords
Random Generator; Genetic Algorithm; Weapon-Target Allocation; Heuristic; population Initialization;
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Times Cited By KSCI : 1  (Citation Analysis)
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1 Dorigo, M., Maniezzo and Colorni, A., "The ant system : an autocatalyic optimizing process," Technical Report 91-016 Revised, Dipartimento di Elettronica, Politecnico di Milano, 1991.
2 Kirkpatrick, S, Gelatt, C. D and Vecchi, M. P, "Optimization by Simulated Annealing," Science 220, pp. 671-680, 1983.   DOI   ScienceOn
3 Fred Glover, "Tabu Search-Part 1," ORSA Journal on Computing, vol. 1, no. 2, pp. 190-206, 1989.   DOI
4 Fred Glover, "Tabu Search-Part 2," ORSA Journal on Computing, vol. 2, no. 1, pp. 4-32, 1990.   DOI
5 J. Kennedy and R. Eberhart, "Particle Swarm Optimization," IEEE International Conference Neural Network, vol. 4, pp. 1942-1948, 1995.
6 D.E. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning, Addison- Wesley Publishing Company Inc, 1989.
7 Kyung-Youb Kwon and Joongseon Joh, "Weapon-Target Assignment Using Genetic Algorithm," Proceeding of KFIS Fall Conference, vol. 13, no. 5, 2003.
8 Ji-Hong Yang and Myung-Mook Han, "The Intelligent Intrusion Detection Systems using Automatic Rule-Based Method," Journel of Korean Institute of Intelligent Systems, vol. 12, no. 6, pp. 531-536, 2002.   DOI
9 Heikki Maaranen, Kaisa Miettinen and Antti Penttinen, "On initial populations of a genetic algorithm for continuous optimization problems," Journal of Global Optimization, vol. 37, no. 3, pp. 405-436, 2007.   DOI
10 Stephane Paradis, Abder Rezak Benaskeur, Martin Oxenham, and Philip Cutler, "Threat evaluation and weapons allocation in network-centric warfare," In Proceedings of the 8th International Conference on Information Fusion, vol. 2, no. 2, 2005.
11 George G. den Broeder, R. E. Ellison, and L. Emerling, "On optimum target assignments," Operations Research, vol. 7, no. 3, pp. 322-326, 1959.   DOI
12 Matsumoto, M., Nishimura, T, "Mersenne twister: a 623-dimensionally equidistributed uniform pseudo- random number generator," ACM Transactions on Modeling and Computer Simulation, vol. 8, no. 1, pp. 3-30, 1998.   DOI
13 Diggle, P.J., Statistical Analysis of Spatial Point Patterns, Academic Press, 1983.
14 Fredrik Johansson, Evaluating the Performance of TEWA Systems, Ph.D Thesis Orebro University, 2010.
15 Ripley, B.D, Spatial Statistics, John Wiley & Sons, 1981.