多兵种联合作战战役任务计划方法研究
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摘要
由于多兵种联合作战战役任务计划的高度不确定性、复杂性以及时间紧迫性等特点,使联合作战任务计划成为作战指挥不可缺少的过程。在当前多兵种联合作战过程中,利用计算机进行联合作战任务计划的辅助生成,是提高指挥员的谋略水平与提高指挥能力,促进决策更加科学化和军事理论研究发展的重要手段。但应用于任务计划的算法还比较零乱,不成体系,更谈不上标准,这也不同程度地降低了作战指挥人员决策的高效性。本文以登岛作战为案例,首先在作战使命下达后,对总使命进行了任务分解,使之成为可具体执行的子任务。然后,对各子任务进行平台资源分配,而这一过程中要解决的关键问题是在平台资源发生冲突的情况下,如何进行任务调度,才能减少冲突、提高任务的分配和执行效率,目前常用来解决这一问题的算法是MDLS算法,本文对此算法进行了详细的描述和研究,指出了其中的不足之处,并从不同角度对MDLS算法进行了改进研究。同时,初步实现了算法运行的模拟系统。
Because of the uncertainty, complexity and time pressure of the task planning in joint campaign, task planning in joint campaign has been indispensable to campaign command. During the joint campaign, using computer to help making the plan of the mission is necessary. It is the important means to enhance the competence of the compere in ruse and command, to promote the decision-making more scientific and to accelerate the development of the martial theory. But the algorithm of task planning is comparatively disorderly and is to say nothing of standard. This reduces the efficiency of decision-making of the campaign compere. This paper takes an example of the campaign of island landing, decomposes the mission into the subtasks which can be performed immediately after the mission is being delivered. Then, the key problem to be solved in platform resource assigning in joint campaign is how to attemper the subtasks can reduce the platform resource conflicts and increase the efficiency in assigning and performing the subtasks. Currently, MDLS algorithm is usually used to solve the problem. This paper introduces the MDLS algorithm in detail, also points out its deficiency and improves the algorithm in different point of view. The simulating system to run the algorithm has been realized.
Because of the uncertainty, complexity and time pressure of the task planning in joint campaign, task planning in joint campaign has been indispensable to campaign command. During the joint campaign, using computer to help making the plan of the mission is necessary. It is the important means to enhance the competence of the compere in ruse and command, to promote the decision-making more scientific and to accelerate the development of the martial theory. But the algorithm of task planning is comparatively disorderly and is to say nothing of standard. This reduces the efficiency of decision-making of the campaign compere. This paper takes an example of the campaign of island landing, decomposes the mission into the subtasks which can be performed immediately after the mission is being delivered. Then, the key problem to be solved in platform resource assigning in joint campaign is how to attemper the subtasks can reduce the platform resource conflicts and increase the efficiency in assigning and performing the subtasks. Currently, MDLS algorithm is usually used to solve the problem. This paper introduces the MDLS algorithm in detail, also points out its deficiency and improves the algorithm in different point of view. The simulating system to run the algorithm has been realized.
引文
[1] Dong-Sheng Yang, Yinlong Lu, and Zhong Liu. Research on Algorithms of Task scheduling. ICMLC2004, IEEE Press, ShangHai, 4-5 August 8 2004. pp: 42-47
[2] Levchuk Y. N, Levchuk G. M, K. R. Pattipati. A Systematic Approach to Optimize Organizations Operating in Uncertain Environments: Design Methodology and Applications. Proceedings of the 7-th International Command & Control Research & Technology Symposium, 2002, Quebec City, QC, Canada, Sept, 2002.
[3] Levchuk, G. M., Y. N. Levchuk, Jie Luo, K. R. Pattipati, and D. L. Kleinman, "Normative Design of Organizations-Part Ⅰ: Mission Planning", in IEEE Transactions on Systems, Man, and Cybernetics, Vol. 32, No. 3, May 2002, pp. 346-359.
[4] Jin Weixin. The Architecture and Implementation of the Distributed Intelligent Integrated Virtual Simulation Information Network of the joint operations[C]. Proceedings of the 2002 International Conference of Scientific Compution, International Academic Press
[5] Colin R Mason. An Angent Architecture for Implementing Command and Control in Military Simulations[C]. Proceedings of the 2001 Winter Simulation Conference, B A Peters, J S Smith, D J Medeiros, and M W Robrer, eds
[6] George Stone, Gregory A MeIntyre. The Joint Warfare System(JWARS): A Modeling and Analysis Tool for the Defense Department[C]. Proceedings of the 2001 Winter Simulation Conference, B A Peters, J S Smith, D J Medeiros and M w Robrer, des
[7] G. M. Levchuk, Y. N. Levchuk, J. Luo, F. Tu, and K. R. Pattipati, A library of optimization algorithms for organizational design. Proceedings of the 2000 Command and Control Research and Technology Symposium. Monterey, CA: NPS, June 2000
[8] Levchuk, Y. N. and Pattipati K. R., Designing Adaptive Organizations to Process a Complex Mission: Algorithms and Applications, submitted to 1997 Command & Control Research & Technology Symposium, Monterey, CA, June 1998
[9] Manimaran, G., Murthy, C. S. R. An efficient dynamic scheduling algorithm for multiprocessor real-time systems. IEEE Transactions on Parallel and Distributed Systems, 1998, 9(3): 312～319
[10] Muthucumaru Maheswaran and Howard Jay Siegel. A Dynamic Matching and Scheduling Algorithm for Heterogeneous Computing Systems. HCW'98, pages 57-69, Orlando, USA, March 1998. IEEE Computer Society Press
[11] Curry, M. L., Kleinman, D. K., and Pattipati, K. R., Mission Modeling, Proceedings of the 1997 Command & Control Research & Technology Symposium, Washington, DC, June 1997
[12] Bertsekas, D. P., Tsitsiklis, J. N., and Wu, C., Rollout Algorithms For Combinatorial Optimization, Journal of Heuristics, Vol. 3, 1997
[13] Kemple W G, Kleinman D L, Berigan M C. A2C2 Initial experiment: Adaptation of the Joint Scenario and Formalization. Proceedings of the 1996 Command & Control Research & Technology Symposium, Monterey, CA, June 1996, pp. 837-846
[14] Hyunok Oh and Soonhoi Ha. A Static Scheduling Heuristic for Heterogeneous Processors. Proceedings of Europar'96, volume 1124 of Lecture Notes in Computer Science, pages 573-577, Lyon, France, August 1996. Springer-Verlag
[15] Volker Strassen. Gaussian Elimination is not Optimal. Numerische Mathematik, 14(3): 354-356, 1996
[16] Kleinman D L, Young P, and Higgins G S. The DDD-Ⅲ: A tool for empirical research in adaptive organizations[A]. Proc. Command and Control Research and Technology Symp[C], Monterey, CA, June 1996
[17] Golub, H., and Van Loan, C. F., Matrix Computations, John Hopkins University Press, Baltimore, Maryland, 1996
[18] Kemple, W. G., Kleinman, D. L., and Berigan, M. C., A2C2 Initial Experiment: Adaptation of the Joint Scenario and Formalization, Proceedings of the 1996 Command & Control Research & Technology Symposium, Monterey, CA, June 1996, pp. 837-846
[19] Simon, H. A., The Sciences of the Artificial, The MIT Press, Cambridge, Massachusetts, 1996
[20] J. Current, Jr, H. Pirkul, and E. Rolland, "Efficient algorithms for solving the shortest covering path problem," Transp. Sci., vol. 28, no. 4, pp. 317-325, 1994
[21] H. El-Rewini, Task Scheduling in Parallel and Distributed Systems. Englewood City, CA: Benjamin Cummings, 1994
[22] Gilbert Sih and Edward Lee. A Compile-Time Scheduling Heuristic for Interconnection constrained Heterogeneous Processor Architectures. IEEE Transactions on Parallel and Distributed Systems, 4(2): 175-187, 1993
[23] Ramamritham, K. J, Stankovic, A., Shiah, P. -F. Efficient scheduling algorithms for real-time multiprocessor systems. IEEE Transactions on Parallel and Distributed Systems, 1990, 1(2): 184～194
[24] B. Shirazi et al. Analysis and evaluation of Heuristic methods for static task scheduling. J. of parallel and distributed computing 10, 1990, 222-232
[25] Boutilier, C., Brafman, R. I., & Geib, C. "Prioritized goal decomposition of Markov decision processes: Toward a synthesis of classical and decision theoretic planning," Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, pp. 1156-1162, Nagoya, Japan. 1990
[26] K. R. Davis, "Resource constrained project scheduling with multiple objectives: A decision support approach," Comput. Oper. Res., vol. 19, no. 7, pp. 655-659, 1990
[27] 王永炎 王强 王宏安等.基于优先级表的实时调度算法及其实现[J].软件学报,2004,15(3):360-370
[28] 鲁音隆 阳东升等.联合战役规划中资源调度算法研究.火力与指挥控制,2004,已录用
[29] 乔颖,王宏安,戴国忠,一种新的实时多处理器系统的动态调度算法[J],软件学报,2002,13(1):51-58
[30] 段永强,曹键,张申生,工作流系统中的任务调度[J],中国机械工程,2002,13(3):233-235转241
[31] 杨红红,吴智铭,基于自适应遗传算法的柔性动态调度研究[J],中国机械工程,2002,13(21):1845-1848
[32] 白书忠,适应未来军事斗争需要,推动应急机动卫勤力量建设再上新台阶,解放军卫勤杂志,2002,4(1):190-193
[33] 金伟新,信息战仿真训练系统的结构设计与技术实现[J],计算机仿真,2002-3,19(2):1-3
[34] 金伟新,新一代联合作战仿真系统结构研究[J],系统仿真技术及应用,中国科学技术大学出版社,2002-4
[35] 鲁云敏、李军、姚一,野战医疗队海上卫勤保障训练的初步实践与体会,解放军卫勤杂志,2001,3(3):149-150
[36] 胡晓峰,金伟新,美军训练模拟[M],国防大学出版社,2001-3
[37] 侯印鸣等,综合电子战-现代战争的钉手锏,国防工业出版社,2001
[38] 初元章、陈勇、曹文献,登岛战役卫勤保障探讨,解放军卫勤杂志,2000,2(2):81-84
[39] 汪江淮,论联合战役作战指挥[M],国防大学出版社,1999
[40] 郁树胜,论联合战役,国防大学出版社,1997-6
[41] 刘桂芳,冯毅,高技术条件下的C~3Ⅰ军事指挥自动化[M],国防大学出版社,1994
[42] 陈亮等,一类实用的军事辅助决策模式[C],高技术与军事系统工程,军事出版社,1993
[43] 李友善,李军,模糊控制理论及其在过程控制中的应用[M],国防工业出版社,1993
[44] 管继先,高技术局部战争战役[M],国防大学出版社,1993,118-145
[45] 姚党鐤,论作战指挥的科学决策[D],国防大学,1992
[2] Levchuk Y. N, Levchuk G. M, K. R. Pattipati. A Systematic Approach to Optimize Organizations Operating in Uncertain Environments: Design Methodology and Applications. Proceedings of the 7-th International Command & Control Research & Technology Symposium, 2002, Quebec City, QC, Canada, Sept, 2002.
[3] Levchuk, G. M., Y. N. Levchuk, Jie Luo, K. R. Pattipati, and D. L. Kleinman, "Normative Design of Organizations-Part Ⅰ: Mission Planning", in IEEE Transactions on Systems, Man, and Cybernetics, Vol. 32, No. 3, May 2002, pp. 346-359.
[4] Jin Weixin. The Architecture and Implementation of the Distributed Intelligent Integrated Virtual Simulation Information Network of the joint operations[C]. Proceedings of the 2002 International Conference of Scientific Compution, International Academic Press
[5] Colin R Mason. An Angent Architecture for Implementing Command and Control in Military Simulations[C]. Proceedings of the 2001 Winter Simulation Conference, B A Peters, J S Smith, D J Medeiros, and M W Robrer, eds
[6] George Stone, Gregory A MeIntyre. The Joint Warfare System(JWARS): A Modeling and Analysis Tool for the Defense Department[C]. Proceedings of the 2001 Winter Simulation Conference, B A Peters, J S Smith, D J Medeiros and M w Robrer, des
[7] G. M. Levchuk, Y. N. Levchuk, J. Luo, F. Tu, and K. R. Pattipati, A library of optimization algorithms for organizational design. Proceedings of the 2000 Command and Control Research and Technology Symposium. Monterey, CA: NPS, June 2000
[8] Levchuk, Y. N. and Pattipati K. R., Designing Adaptive Organizations to Process a Complex Mission: Algorithms and Applications, submitted to 1997 Command & Control Research & Technology Symposium, Monterey, CA, June 1998
[9] Manimaran, G., Murthy, C. S. R. An efficient dynamic scheduling algorithm for multiprocessor real-time systems. IEEE Transactions on Parallel and Distributed Systems, 1998, 9(3): 312～319
[10] Muthucumaru Maheswaran and Howard Jay Siegel. A Dynamic Matching and Scheduling Algorithm for Heterogeneous Computing Systems. HCW'98, pages 57-69, Orlando, USA, March 1998. IEEE Computer Society Press
[11] Curry, M. L., Kleinman, D. K., and Pattipati, K. R., Mission Modeling, Proceedings of the 1997 Command & Control Research & Technology Symposium, Washington, DC, June 1997
[12] Bertsekas, D. P., Tsitsiklis, J. N., and Wu, C., Rollout Algorithms For Combinatorial Optimization, Journal of Heuristics, Vol. 3, 1997
[13] Kemple W G, Kleinman D L, Berigan M C. A2C2 Initial experiment: Adaptation of the Joint Scenario and Formalization. Proceedings of the 1996 Command & Control Research & Technology Symposium, Monterey, CA, June 1996, pp. 837-846
[14] Hyunok Oh and Soonhoi Ha. A Static Scheduling Heuristic for Heterogeneous Processors. Proceedings of Europar'96, volume 1124 of Lecture Notes in Computer Science, pages 573-577, Lyon, France, August 1996. Springer-Verlag
[15] Volker Strassen. Gaussian Elimination is not Optimal. Numerische Mathematik, 14(3): 354-356, 1996
[16] Kleinman D L, Young P, and Higgins G S. The DDD-Ⅲ: A tool for empirical research in adaptive organizations[A]. Proc. Command and Control Research and Technology Symp[C], Monterey, CA, June 1996
[17] Golub, H., and Van Loan, C. F., Matrix Computations, John Hopkins University Press, Baltimore, Maryland, 1996
[18] Kemple, W. G., Kleinman, D. L., and Berigan, M. C., A2C2 Initial Experiment: Adaptation of the Joint Scenario and Formalization, Proceedings of the 1996 Command & Control Research & Technology Symposium, Monterey, CA, June 1996, pp. 837-846
[19] Simon, H. A., The Sciences of the Artificial, The MIT Press, Cambridge, Massachusetts, 1996
[20] J. Current, Jr, H. Pirkul, and E. Rolland, "Efficient algorithms for solving the shortest covering path problem," Transp. Sci., vol. 28, no. 4, pp. 317-325, 1994
[21] H. El-Rewini, Task Scheduling in Parallel and Distributed Systems. Englewood City, CA: Benjamin Cummings, 1994
[22] Gilbert Sih and Edward Lee. A Compile-Time Scheduling Heuristic for Interconnection constrained Heterogeneous Processor Architectures. IEEE Transactions on Parallel and Distributed Systems, 4(2): 175-187, 1993
[23] Ramamritham, K. J, Stankovic, A., Shiah, P. -F. Efficient scheduling algorithms for real-time multiprocessor systems. IEEE Transactions on Parallel and Distributed Systems, 1990, 1(2): 184～194
[24] B. Shirazi et al. Analysis and evaluation of Heuristic methods for static task scheduling. J. of parallel and distributed computing 10, 1990, 222-232
[25] Boutilier, C., Brafman, R. I., & Geib, C. "Prioritized goal decomposition of Markov decision processes: Toward a synthesis of classical and decision theoretic planning," Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, pp. 1156-1162, Nagoya, Japan. 1990
[26] K. R. Davis, "Resource constrained project scheduling with multiple objectives: A decision support approach," Comput. Oper. Res., vol. 19, no. 7, pp. 655-659, 1990
[27] 王永炎 王强 王宏安等.基于优先级表的实时调度算法及其实现[J].软件学报,2004,15(3):360-370
[28] 鲁音隆 阳东升等.联合战役规划中资源调度算法研究.火力与指挥控制,2004,已录用
[29] 乔颖,王宏安,戴国忠,一种新的实时多处理器系统的动态调度算法[J],软件学报,2002,13(1):51-58
[30] 段永强,曹键,张申生,工作流系统中的任务调度[J],中国机械工程,2002,13(3):233-235转241
[31] 杨红红,吴智铭,基于自适应遗传算法的柔性动态调度研究[J],中国机械工程,2002,13(21):1845-1848
[32] 白书忠,适应未来军事斗争需要,推动应急机动卫勤力量建设再上新台阶,解放军卫勤杂志,2002,4(1):190-193
[33] 金伟新,信息战仿真训练系统的结构设计与技术实现[J],计算机仿真,2002-3,19(2):1-3
[34] 金伟新,新一代联合作战仿真系统结构研究[J],系统仿真技术及应用,中国科学技术大学出版社,2002-4
[35] 鲁云敏、李军、姚一,野战医疗队海上卫勤保障训练的初步实践与体会,解放军卫勤杂志,2001,3(3):149-150
[36] 胡晓峰,金伟新,美军训练模拟[M],国防大学出版社,2001-3
[37] 侯印鸣等,综合电子战-现代战争的钉手锏,国防工业出版社,2001
[38] 初元章、陈勇、曹文献,登岛战役卫勤保障探讨,解放军卫勤杂志,2000,2(2):81-84
[39] 汪江淮,论联合战役作战指挥[M],国防大学出版社,1999
[40] 郁树胜,论联合战役,国防大学出版社,1997-6
[41] 刘桂芳,冯毅,高技术条件下的C~3Ⅰ军事指挥自动化[M],国防大学出版社,1994
[42] 陈亮等,一类实用的军事辅助决策模式[C],高技术与军事系统工程,军事出版社,1993
[43] 李友善,李军,模糊控制理论及其在过程控制中的应用[M],国防工业出版社,1993
[44] 管继先,高技术局部战争战役[M],国防大学出版社,1993,118-145
[45] 姚党鐤,论作战指挥的科学决策[D],国防大学,1992
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