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Research On Modeling And Optimization Methods For Military Mission Planning Under Uncertainty

Posted on:2015-01-12Degree:DoctorType:Dissertation
Country:ChinaCandidate:Y X ZhangFull Text:PDF
GTID:1226330479979535Subject:Army commanding learn
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With the constraints of a series of alternative tasks and limited resources, the problem of military mission planning(MMP) deals with selecting a sequence of tasks that accomplish the mission planning and allocating limited resources to the given tasks with the objective of optimizing some performance measures. The scientific and effective MMP results could conduct the whole resources to execute their respective tasks to achieve the total objective in different space and time. However, the complexity of the MMP and the uncertainty of the battlefield increase the difficulty of the resolving works. The correctness, timing and stabilization of the MMP schedule are faced with great challenges. Hence, we need to study the scientific and effective resolving methods for the MMP problem.The existing studies of the MMP problem under uncertainty mainly concerns with how to adjust the schedule after the disruption occurs, so as to keep its feasibility and good efficiency. This method implements easily and could deal with various disruptions, but it induces the result of continually modifying the baseline schedule. In this paper, we focus with the study of how to obtain a proactive MMP schedule by accounting the uncertainty before the disruptions occur, so as to reduce the probability of adjusting in the implementing process. The main work and innovations are presented as follows:(1) The model and resolving framework for the military mission planning(MMP) problem under uncertaintyThe mostly uncertain factors of the MMP problem under uncertainty are discussed, including the task uncertainty which constitute the mission, the resource uncertainty of the availability amount and the task duration uncertainty, and their quantitative description method are studied. Based on the analysis of the constituents of the MMP problem, the formalized description of the MMP problem model is constructed. Then, the key problems of the MMP problem are discussed, including the construction of the military Course of Action, the military task planning and the military resource allocation and their relationship are analyzed. Finally, the resolving framework of the MMP problem is constructed.(2) The resolving and optimization methods for the military Course of Action under task uncertaintyThe problem of military Course of Action under task uncertainty deals with selecting a sequence of tasks that accomplish a given objective with the limited resource constraints. The task uncertainty is described by the P/A networks and the problem is transformed into constraint Satisfiability(SAT) problem by transforming the task selection problem into 0/1 evaluating problem. A logical task graph is proposed to induce the complexity of the problem. The classical SAT algorithm of DPLL is used to resolving the problem, and it is also expanded by accounting the knowledge of resource constraint.(3) The resolving and optimization methods for the military task planning problem under resource uncertaintyThe problem of military task planning under resource uncertainty concerns with the allocation of limit resources to tasks with the objective of optimizing some performance measures. The resource uncertainty is quantitatively described by the probability distribution, and resolved by adopting the resource buffering strategy. Then, a multi-objective evolutional heuristic is proposed to resolve the problem based on the multi-objective optimization theory. During the resolving process, a rule-based heuristic is also proposed to quickly construct the initial schedule.(4) The resolving and optimization methods for the military resource allocation problem under time uncertaintyThe problem of military resource allocation under time uncertainty deals with optimizing the resource translation between their executing tasks. The task duration uncertainty is quantitatively described by the probability distribution, and resolved by the strategies of robust resource allocation and time buffering. Firstly, the construction methods for the resource flow network are analyzed and a rule-based heuristic is proposed to construct a robust schedule. Then, a time buffering heuristic is proposed for inserting time buffers in the baseline schedule.
Keywords/Search Tags:military mission planning, military task scheduling, military resource allocation, military course of action, uncertain optimization, multi-objective evolutionary algorithm
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