DocumentCode :
2917754
Title :
Multi-platform coordinated mission planning under uncertainties
Author :
Tang, Luohao ; Zhang, Weiming ; Zhu, Cheng ; Huang, JinCai
Author_Institution :
Sci. & Technol. on Inf. Syst. Eng. Lab., Nat. Univ. of Defense Technol., Changsha, China
fYear :
2011
fDate :
5-8 Dec. 2011
Firstpage :
277
Lastpage :
282
Abstract :
Military mission planning aims to coordinate a set of platforms with different capacities to accomplish a set of tasks under temporal, spatial and resource constraints. However, as military operations are intrinsically dynamic and uncertain, a solution (plan) corresponding to the deterministic circumstance is fragile due to unexpected events. To tackle this problem, this paper proposes a chance constrained programming model, which incorporates many uncertain factors, such as the durations, locations and resource requirements of tasks. The objective of mission planning is to coordinate the platforms to maximize the probability that all of tasks are completed successfully while satisfying the chance constraints. The problem is solved under a computational framework combining GA and Monte Carlo Simulation, the GA is used to solve the platform allocation and task scheduling while Monte Carlo Simulation is used to process the chance constraints. A mission instance is presented which demonstrates the usefulness of the proposed model and algorithm.
Keywords :
Monte Carlo methods; genetic algorithms; military systems; operations research; scheduling; GA; Monte Carlo simulation; chance constrained programming model; computational framework; military mission planning; military operations; multiplatform coordinated mission planning; platform allocation; resource constraint; spatial constraint; task scheduling; temporal constraint; Biological cells; Genetic algorithms; Modeling; Monte Carlo methods; Planning; Resource management; Routing; GA and Monte Carlo Simulatio; chance constrained programming; mission planning; uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Hybrid Intelligent Systems (HIS), 2011 11th International Conference on
Conference_Location :
Melacca
Print_ISBN :
978-1-4577-2151-9
Type :
conf
DOI :
10.1109/HIS.2011.6122118
Filename :
6122118
Link To Document :
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