최소 단어 이상 선택하여야 합니다.
최대 10 단어까지만 선택 가능합니다.
다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
NTIS 바로가기Journal of Korean Society of Industrial and Systems Engineering = 한국산업경영시스템학회지, v.39 no.2, 2016년, pp.88 - 102
이대력 (서울시립대학교 경영학과) , 양재환 (서울시립대학교 경영학부)
This paper considers the allocation and engagement scheduling problem of interceptor missiles, and the problem was formulated by using MIP (mixed integer programming) in the previous research. The objective of the model is the maximization of total intercept altitude instead of the more conventional...
핵심어 | 질문 | 논문에서 추출한 답변 |
---|---|---|
염색체를 이진수로 표현한 것은 무엇 때문인가? | 염색체를 이진수로 표현한 것은 수선 연산에서 이진수가 십진수보다 편리하기 때문이다. | |
알고리즘의 신뢰성 향상을 위해 여러 번 계산하더라도 동일 수준의 최적해를 산출할 수 있도록 개선되어야 하는 이유는? | 그러므로 더 빠른 실행 시간을 가질 수 있도록 개선되어야 한다. 둘째, 유전 알고리즘의 특성 상 초기 해집단의 생성 결과에 따라 실행 시간과 해의 값에 차이가 발생하는데, 문제의 크기가 커질수록 이 차이는 증가한다. 따라서 알고리즘의 신뢰성 향상을 위해 여러 번 계산하더라도 동일 수준의 최적해를 산출할 수 있도록 개선되어야 한다. | |
한국형 미사일 방어체계의 구성은? | 우리나라에서 구축 중인 한국형 미사일 방어체계(KAMD, Korea Air and Missile Defense)는 조기경보체계, 지휘통제체계, 요격체계로 구성되는데, 이 중에서 지휘통제체계 역할을 수행하는 곳을 작전통제소라고 한다[24]. 작전통제소는 각종 탐지장치로부터 탐지된 적 탄도미사일의 정보를 수집 및 분석하고, 전국에 배치되어 있는 요격포대의 위치와 상태를 파악해서 어느 포대에서 몇 발의 요격미사일을 발사할 것인지 요격명령을 내리게 된다. |
Ahner, D.K. and Parson, C.R., Optimal multi-stage allocation of weapons to targets using adaptive dynamic programming, Optimization Letters, 2015, Vol. 9, No. 8, pp. 1689-1701.
Ahuja, R.K., Kumar, A., Jha, K.C., and Orlin, J.B., Exact and heuristic algorithms for the weapon-target assignment problem, Operations Research, 2007, Vol. 55, No. 6, pp. 1136-1146.
Chen, H., Liu, Z., Sun, Y., and Li, Y., Particle swarm optimization based on genetic operators for sensor-weapon-target assignment, 2012 Fifth International Symposium on Computational Intelligence and Design, 2012, pp. 170-173.
Chen, J., Xin, B., Peng, Z.H., Dou, L.H., and Zhang, J., Evolutionary decision-makings for the dynamic weapontarget assignment problem, Science in China Series F : Information Sciences, 2009, Vol. 52, No. 11, pp. 2006-2018.
Coello, C.A., Theoretical and numerical constraint- handling techniques used with evolutionary algorithms : a survey of the state of the art, Computer Methods in Applied Mechanics and Engineering, 2002, Vol. 191, pp. 1245-1287.
Fu, T., Liu, Y., and Chen, J., Improved genetic and ant colony optimization algorithm for regional air defense WTA problem, Proceedings of the First International Conference on Innovative Computing, Information and Control, 2006, pp. 226-229.
Geetha, S., A hybrid particle swarm optimization with genetic operators for vehicle routing problem, Journal of Advances in Information Technology, 2010, Vol. 1, No, 4, pp. 181-188.
Gulez, T., Weapon-target allocation and scheduling for air defense with time varying hit probabilities [master's thesis]. [Ankara, Turkey] : Middle East Technical University, 2007.
Hosein, P., A class of dynamic nonlinear resource allocation problems [dissertation], [Cambridge, Massachusetts, United States] : Massachusetts Institute of Technology, 1989.
Jang, J.G., Kim, K., Choi, B.W., and Suh, J.J., A linear approximation model for an asset-based weapon target assignment problem, Journal of Society of Korea Industrial and Systems Engineering, 2015, Vol. 38, No. 5, pp. 108-116.
Julstrom, B.A., String-and permutation-coded genetic algorithms for the static weapon-target assignment problem, Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference, 2009, pp. 2553-2558.
Jung, H.S., Ballistic Missile Defense, Journal of the Defense Science and Technology Information, 2013, Vol. 40, p. 169.
Karasakal, O., Optimal air defense strategies for a naval task group [dissertation], [Ankara, Turkey] : Middle East Technical University, 2004.
Khosla, D., Hybrid genetic approach for the dynamic weapon-target allocation problem, Proceedings of SPIE, 2001, Vol. 4396, pp. 244-259.
Kim, M.S., The missiles that occupy news, KAMD and Kill Chain, Geunduun, 2013, Vol. 59, pp. 14-17.
Krokhmal, P., Murphey, R., Pardalos, P., and Uryasev, S., Use of conditional value-at-risk in stochastic programs with poorly defined distributions, S. Butenko et al.(Eds.). Recent Developments in Cooperative Control and Optimization, Kluwer Academic Publishers, 2004, pp. 225-243.
Lee, J.B., A study on real time dynamic multi-weapon multi-target assignment algorithm [dissertation]. [Taejeon, Korea] : Korea Advanced Institute Science and Technology, 2009.
Lee, M.Z., Constrained weapon-target assignment : enhanced very large scale neighborhood search algorithm, IEEE Transactions on Systems Man and Cybernetics-Part A Systems and Humans, 2010, Vol. 40, No. 1, pp. 198-204.
Lee, Z.J., Lee, C.Y., and Suc, S.F., An immunity-based ant colony optimization algorithm for solving weapon- target assignment problem, Applied Soft Computing, 2002, Vol. 2, No. 1, pp. 39-47.
Liu, C., Wang, H., and Qiu Z., An adaptive memetic algorithm solving dynamic weapon target assignment problem, IEEE International Conference on Information Engineering and Computer Science, 2010, pp. 1-4.
Liu, P., Xiong, J., and Zhang, W., WTA model study of air defense missile system based on particle algorithm, Proceedings of IEEE Chinese Guidance, Navigation and Control Conference, Yantai, China, 2014, pp. 1534-1538.
Ministry of National Defense(Republic of Korea), Defense White Paper, 2014, pp. 58-59.
Moon, B.R., Easy Learning Genetic Algorithms. Seoul, Korea : Hanbit Media Inc., 2008, pp. 59-61.
Murphey, R.A., "An approximate algorithm for a weapon target assignment stochastic program," in Approximation and Complexity in Numerical Optimization : Continuous and Discrete Problems, Kluwer Academic Publishers, 1999, pp. 1-16.
Song, Z., Zhu, F., and Zhang, D., A heuristic genetic algorithm for solving constrained weapon-target assignment problem, IEEE International Conference on Intelligent Computing and Intelligent Systems, 2009, pp. 336-341.
Teng, P., Lv, H., Huang, J., and Sun, L., Improved particle swarm optimization algorithm and its application in coordinated air combat missile-target assignment, Proceedings of the 7th World Congress on Intelligent Control and Automation, 2008, pp. 2833-2837.
Woo, B.-H., Reinforced Genetic Algorithm for Solving Reliability Optimization Design Problem, Journal of the Korean Institute of Plant Engineering, 2012, Vol. 17, No. 4, pp. 17-33.
Xin, B. and Chen. J., An Estimation of Distribution Algorithm with Efficient Constructive Repair/Improvement Operator for the Dynamic Weapon-Target Assignment, Proceedings of the 31st Chinese Control Conference, Hefei, China, 2012, pp. 2346-2351.
Xin, B., Chen J., Peng, Z., Dou, L., and Zhang, J., An efficient rule-based constructive heuristic to solve dynamic weapon-target assignment problem, IEEE Transactions on Systems, Man, and Cybernetics-Part A : Systems and Humans, 2011, Vol. 41, No. 3, pp. 598-606.
You, H.-S., A performance improvement study on weapon assignment of fire control system [master's thesis], [Seoul, Korea] : Hanyang University, 2014.
Zhang, J., Xu, C., Wang, X., and Yuan, D., ACGA algorithm of solving weapon-target assignment problem, Open Journal of Applied Sciences, 2012, Vol. 2, No. 4, pp. 74-77.
Zhu, B., Zou, F., and Wei, J., A novel approach to solving weapon-target assignment problem based on hybrid particle swarm optimization algorithm, International Conference on Electronic and Mechanical Engineering and Information Technology, 2011, pp. 1385-1387.
*원문 PDF 파일 및 링크정보가 존재하지 않을 경우 KISTI DDS 시스템에서 제공하는 원문복사서비스를 사용할 수 있습니다.
Free Access. 출판사/학술단체 등이 허락한 무료 공개 사이트를 통해 자유로운 이용이 가능한 논문
※ AI-Helper는 부적절한 답변을 할 수 있습니다.