請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/66836完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 孔令傑(Ling-Chieh Kung) | |
| dc.contributor.author | Hsin-Cheng Fang | en |
| dc.contributor.author | 方心成 | zh_TW |
| dc.date.accessioned | 2021-06-17T01:09:14Z | - |
| dc.date.available | 2021-02-05 | |
| dc.date.copyright | 2020-02-05 | |
| dc.date.issued | 2020 | |
| dc.date.submitted | 2020-01-20 | |
| dc.identifier.citation | 1. Ahuja, R. K., A. Kumar, K. C. Jha, J. B. Orlin. 2007. Exact and heuristic algorithms for the weapon-target assignment problem. Operations research 55(6) 1136–1146.
2. Bogdanowicz, Z. R. 2009. A new efficient algorithm for optimal assignment of smart weapons to targets. Computers & Mathematics with Applications 58(10) 1965–1969. 3. Bogdanowicz, Z. R., N. P. Coleman. 2007. Sensor-target and weapon-target pairings based on auction algorithm. Proceedings of the 11th WSEAS International Conference on Applied Mathematics. World Scientific and Engineering Academy and Soc.(WSEAS) Stevens Point, WI, 92–96. 4. Bogdanowicz, Z. R., A. Tolano, K. Patel, N. P. Coleman. 2012. Optimization of weapon–target pairings based on kill probabilities. IEEE Transactions on Cybernetics 43(6) 1835–1844. 5. Bradford, J. C. 1961. Determination of optimal assignment of a weapon system to several targets. AEREITM-9, Vought Aeronautics, Dallas, Texas. 6. Cai, H., J. Liu, Y. Chen, H. Wang. 2006. Survey of the research on dynamic weapon-target assignment problem. Journal of Systems Engineering and Electronics 17(3) 559–565. 7. Chang, S. C., R. M. James, J. J. Shaw. 1987. Assignment algorithm for kinetic energy weapons in boost phase defence. 26th IEEE Conference on Decision and Control, vol. 26. IEEE, 1678–1683. 8. Chen, S., J. He, H. Liu. 2012. Realization and simulation of parallel ant colony algorithm to solve wta problem. 2012 International Conference on Systems and Informatics (ICSAI2012). IEEE, 2458–2461. 9. Day, R. H. 1966. Allocating weapons to target complexes by means of nonlinear programming. Operations Research 14(6) 992–1013. 10. denBroeder, Jr., G. G., R. E. Ellison, L. Emerling. 1959. On optimum target assignments. Operations Research 7(3) 322–326. 11. Fei, A. G., L. Y. Zhang, Q. J. Ding. 2012. Multi-aircraft cooperative fire assignment based on auction algorithm. Systems Engineering and Electronics 34(9) 1829–1833. 12. Fredrik, J., F. Göran. 2011. Real-time allocation of firing units to hostile targets. J. Adv. Inf. Fusion 6(2) 187–199. 13. Galati, D. G., M. A. Simaan. 2007. Effectiveness of the nash strategies in competitive multi-team target assignment problems. IEEE Transactions on Aerospace and Electronic Systems 43(1) 126–134. 14. Hsueh, K. Y. 2019. Route Planning for a Military Aircraft considering Risk and Number of Turns. Master’s thesis, National Taiwain University. 15. Julstrom, B. A. 2009. 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: Late Breaking Papers. ACM, 2553–2558. 16. Katter, J. D. 1986. A solution of the multi-weapon. Multi-Target Assignment Problem (Working Paper: 26957), MITRE, Bedford, MA, USA . 17. Kline, A. G., D. K. Ahner, B. J. Lunday. 2019. Real-time heuristic algorithms for the static weapon-target assignment problem. Journal of Heuristics 25(3) 377–397. 18. Kolitz, Stephan E. 1988. Analysis of a maximum marginal return assignment algorithm. Proceedings of the 27th IEEE Conference on Decision and Control. IEEE, 2431–2436. 19. Lee, M. Z. 2009. Constrained weapon–target assignment: Enhanced very large scale neighborhood search algorithm. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans 40(1) 198–204. 20. Lee, Z. J., W. L. Lee. 2003. A hybrid search algorithm of ant colony optimization and genetic algorithm applied to weapon-target assignment problems. International Conference on Intelligent Data Engineering and Automated Learning. Springer, 278–285. 21.Lee, Z. J., S. F. Su, C. Y. Lee. 2002. A genetic algorithm with domain knowledge for weapon-target assignment problems. Journal of the Chinese Institute of Engineers 25(3) 287–295. 22. Li, Y., Y. Kou, Z. Li, A. Xu, Y. Chang. 2017. A modified pareto ant colony optimization approach to solve biobjective weapon-target assignment problem. International Journal of Aerospace Engineering 2017 1–14. 23. Lloyd, S. P., H. S. Witsenhausen. 1986. Weapons allocation is np-complete. 1986 Summer Computer Simulation Conference. 1054–1058. 24. Manne, A. S. 1958. A target-assignment problem. Operations Research 6(3) 346–351. 25. Metler, W. A., F. L. Preston, J. Hofmann. 1990. A suite of weapon assignment algorithms for a sdi mid-course battle manager. Tech. rep., Naval Research Lab Washington DC. 26. Peng, T., Lv. Huigang, J. Huang, S. Liang. 2008. Improved particle swarm optimization algorithm and its application in coordinated air combat missile-target assignment. 2008 7th World Congress on Intelligent Control and Automation. IEEE, 2833–2837. 27. Ruan, M. Z., Q. M. Li, T.H. Liu. 2010. Modeling and optimization on fleet antiaircraft firepower allocation. Tech. rep., Acta Armamentarii. 28. Toet, A., H. D. Waard. 1995. The Weapon-Target Assignment Problem. TNO Human Factors Research Institute. 29. Van deb Bergh, F., A. P. Engelbrecht. 2002. A new locally convergent particle swarm optimiser. IEEE International conference on Systems, Man and Cybernetics, vol. 3. IEEE, 96–101. 30. Wacholder, Eitan. 1989. A neural network-based optimization algorithm for the static weapon-target assignment problem. ORSA Journal on Computing 1(4) 232–246. 31. Xin, B., J. Chen, J. Zhang, L. Dou, Z. Peng. 2010. Efficient decision makings for dynamic weapon-target assignment by virtual permutation and tabu search heuristics. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) 40(6) 649–662. 32. Yu, J. X., S. H. Wang, WX. Cheng. 2008. Target allocation decision making based on improved genetic algorithms with local search. Systems Engineering and Electronics 30(6) 1114–1118. 33. Yuan, H. Y., X. J. Gao. 2012. The weapon target assignment strategy research on genetic algorithm. Proc. 2010 3rd Int. Conf. on Computer and Electrical Engineering, vol. 53. 471–475. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/66836 | - |
| dc.description.abstract | 使用多種武器針對來襲的各個敵方武器進行抵禦和交戰的問題被稱為武器目標分配問題，這類問題自從 1958 年至今已行之有年。本篇研究探討當我軍數架戰鬥機執行空戰任務並遭遇敵軍數架戰機時，應如何分配各機武器以最大化達成任務目標的成功率。在空戰時，各架戰鬥機上擁有多種攻擊性與防禦性武器以影響射出的飛彈的致死率，而戰鬥機在高速環境下位置也快速地改變，因此，解決這類問題的演算法必須即時地求出最佳的武器資源分配方法。研究中提出兩種不同的任務，分別是「攻擊」與「閃躲」，其中前者的目標是最大化敵方損傷，後者則是考慮敵方可能的攻擊行為預先攻擊以最小化敵方對我方的損害。本研究基於粒子群最佳化（Particle Swarm Optimization）建構演算法，並進行多項數值實驗，顯示本篇提出的演算法優於過去研究提出的演算法，並可在極短時間內得出結果。最後，在閃躲任務中也嘗試分析錯估敵方攻擊策略的損失以探討此類目標式的優缺點。 | zh_TW |
| dc.description.abstract | The weapon target assignment (WTA) problem, which assigns multiple weapons to multiple targets, has been studied for decades. In this study, we consider a WTA problem among fighter aircrafts. Each aircraft has multiple types of offensive and defensive weapons. When determining how to coordinate our aircrafts and use their weapons, there can be two types of missions, “attack” and “dodge”, where the former maximizes the enemy’s damage and the latter minimizes our damage. We modify Particle Swarm Optimization to propose one new algorithm to solve this problem in real time. Through numerical experiments, we show that our proposed algorithm is better than existing ones. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T01:09:14Z (GMT). No. of bitstreams: 1 ntu-109-R06725045-1.pdf: 637992 bytes, checksum: aa4784afaab589f69031f2076b1ddbf6 (MD5) Previous issue date: 2020 | en |
| dc.description.tableofcontents | 1 Introduction ... p1
1.1 Background and motivation ... p1 1.2 Research objectives ... p3 1.3 Research plan ... p4 2 Literature Review ... p5 2.1 Weapon target allocation ... p5 2.2 Exact approaches for WTA ... p8 2.3 The Heuristic method for WTA ... p9 3 Problem Description and Formulation ... p11 3.1 Problem statement ... p11 3.2 Formulation ... p16 3.3 Problem reduction ... p17 3.4 Analysis of special case ... p19 4 The Algorithms ... p21 4.1 Greedy approaches ... p21 4.1.1 Maximum marginal return algorithm for static weapon allocation ... p22 4.1.2 Enhanced maximum marginal return for weapon allocation ... p25 4.2 Particle swarm optimization algorithm for static weapon target allocation problem ... p26 4.3 Hybrid approach ... p28 5 Numerical Experiments ... p34 5.1 Experiment design ... p34 5.2 Performance of proposed algorithms ... p35 5.2.1 Benchmarks ... p36 5.2.2 Comparison with optimal solution for small cases ... p37 5.2.3 Comparison among algorithms for large-scale cases ... p39 5.3 Analysis of misunderstanding target strategy ... p40 6 Conclusions and Future Works ... p43 6.1 Conclusions ... p43 6.2 Future works ... p44 Bibliography ... p46 | |
| dc.language.iso | zh-TW | |
| dc.subject | 最佳化演算法 | zh_TW |
| dc.subject | 軍用載具 | zh_TW |
| dc.subject | 作業研究 | zh_TW |
| dc.subject | 武器目標分配 | zh_TW |
| dc.subject | Military Aircraft | en |
| dc.subject | Optimization Research | en |
| dc.subject | Operations Research | en |
| dc.subject | Weapon Target Allocation | en |
| dc.title | 空戰中的實時多機武器目標分配任務 | zh_TW |
| dc.title | Real-time Multi-Aircraft Weapon Target Assignment Missions in an Air Combat | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 108-1 | |
| dc.description.degree | 碩士 | |
| dc.contributor.coadvisor | 陳建錦(Chien-Chin Chen) | |
| dc.contributor.oralexamcommittee | 黃奎隆(Kuei-Lung Huang) | |
| dc.subject.keyword | 軍用載具,武器目標分配,作業研究,最佳化演算法, | zh_TW |
| dc.subject.keyword | Military Aircraft,Weapon Target Allocation,Operations Research,Optimization Research, | en |
| dc.relation.page | 50 | |
| dc.identifier.doi | 10.6342/NTU201904251 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2020-01-20 | |
| dc.contributor.author-college | 管理學院 | zh_TW |
| dc.contributor.author-dept | 資訊管理學研究所 | zh_TW |
| 顯示於系所單位： | 資訊管理學系 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-109-1.pdf 未授權公開取用 | 623.04 kB | Adobe PDF |
系統中的文件，除了特別指名其著作權條款之外，均受到著作權保護，並且保留所有的權利。