潜艇装备作战使用性能双域稳健优化方法研究
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摘要
论证工作处于潜艇装备全寿命周期的前端,其中潜艇装备作战使用性能论证作为连接军事需求与研制方案的桥梁,是论证工作中至关重要的一环。因此,作战使用性能指标的提出既要充分满足军事需求,又要具有较好的方案可行性。而现有的作战使用性能论证过程的一些局限之处,使得一方面难以从有效满足军事需求的角度证明提出的作战使用性能指标值是最优的,另一方面难以从可行性的角度证明提出的作战使用性能指标值是可实现的。这就导致在装备采办的后期阶段,有可能发现在作战使用性能论证阶段做出的决策存在重大失误。但是,此时如果想要对已经做出的决策进行调整,将会付出费用高昂的代价。因此,如何科学合理地从军事需求出发确定潜艇装备作战使用性能的量化要求,并保证所提出的作战使用性能指标具有一定的稳定性,这是一个需要迫切解决的问题。
为了保证潜艇装备作战使用性能论证所提出的作战使用性能指标的量化要求具备相当的稳定性,本文提出了潜艇装备作战使用性能指标的双域稳健最优性的概念,并针对传统的潜艇装备作战使用性能论证模式存在的问题提出了新的潜艇装备作战使用性能双域稳健优化论证模式。具体来说,本文的主要研究内容和成果包括以下几个方面：
(1)面向潜艇装备作战使用性能论证问题,提出了基于群决策的可追溯双域稳健优化(Multi-Expert based, requirement-Traceable dual-domain Robust Optimization,简称METRO)方法论。METRO方法论强调军事需求的牵引作用,作战使用性能论证是以顶层的军事需求为初始的出发点,同时论证结果的验证也是以对于顶层的军事需求的满足程度为最终的落脚点。首先,通过建立军事需求与作战使用性能之间的双向可追溯映射关系,并通过多专家信息融合的方式保证了在认知域内对于这一双向可追溯映射关系的认识具有相当的稳健性。然后,通过建立计算机化的潜艇装备概念方案设计综合模型来反映作战使用性能与概念方案之间的映射关系,并通过不确定性分析保证在物理域内概念方案的稳健性。最后,通过一个优化过程将上述要素集成为一个有着共同目标的协调一致运作的整体,能够以一种系统化的方式解决最终提出的作战使用性能要求的可行性、最优性、稳健性和可追溯性问题。
(2)针对建立军事需求与作战使用性能的双向可追溯映射关系这一问题,提出了基于QFD/ANP和模糊积分的武器装备军事需求映射技术。首先,提出了一种基于QFD和ANP的武器装备作战需求分析模型,能够综合考虑军事需求、作战任务、作战使用性能、国内外同类装备和装备概念方案之间的复杂关系,同时能够以一种统一的和结构化的方式对其中所包含的信息进行处理,提高了判断的准确性和一致性,实现了从顶层的军事需求到底层的作战使用性能的映射。其次,以模糊测度的概念描述作战使用性能之间的相互关系,并提出了一种基于ANP的模糊测度计算方法,适用于没有历史数据可以利用的情况,并且易于专家的理解和操作,大大降低了模糊测度在实际决策问题中的应用难度。最后,在以上研究基础上建立了基于Choquet积分的潜艇装备概念方案军事效用模型,实现了从底层的作战使用性能到顶层的军事需求的映射。
(3)为了在认知域内确保对于所建立的军事需求与作战使用性能指标的双向可追溯映射关系的判断具有稳健性,提出了基于多种形式偏好信息的多专家信息融合及共识技术。首先,研究了多种形式偏好信息的一致化方法,重点研究了多粒度多语义语言判断矩阵的一致化方法,该方法能够保证在任意语言评价集之间的信息无损的转换。这使得专家能够以自己熟悉的形式给出判断信息,有利于获取专家的真实偏好,可以提升决策结果的稳健性。其次,在专家偏好信息一致化的基础上,针对专家偏好可能存在关联关系的问题,提出了一种基于主客观信息的综合赋权方法,能够根据专家知识结构之间的相似度和专家偏好信息之间的相似度,确定专家的重要程度(用2-可加模糊测度的概念对其进行表示),并使用Choquet积分对专家偏好信息进行融合。通过合理确定专家的决策权力,能够获取真实反应群体意见的结果,同样有利于提升决策结果的稳健性。最后,通过对信息融合过程的评价以及对群体共识水平的测度,以反馈的方式引导群体达成共识。
(4)针对在物理域内将备选分系统的不确定因素对于潜艇装备作战使用性能的影响程度进行量化的问题,提出了基于高斯过程元模型的潜艇装备概念方案稳健性评估技术。首先,定义了潜艇装备概念方案的稳健性指标,并基于蒙特卡洛方法对单个概念方案的稳健性指标进行评估。然后,为了解决大量概念方案的稳健性指标评估所带来的严重计算效率问题,提出了基于高斯过程元模型的稳健性评估技术,利用高斯过程元模型构建设计空间中概念方案的稳健性指标值的响应面,能够快速对任意方案的稳健性指标进行评估。针对高斯过程建模中关键的相关函数选择和超参数优化问题,提出了使用混合核函数的策略和基于确定性退火算法的超参数优化方法,与现有的超参数优化算法相比,优化效率和结果精度都有显著提高。
(5)在以上研究基础上,采用基于双响应面的稳健优化策略,并将于边缘分布估计的多目标优化算法(MOMDA)应用于潜艇装备作战使用性能优化问题。最后,以一种多用途攻击型潜艇装备作战使用性能论证为例,应用所提出的方法论和关键技术解决问题,验证了方法的可行性和有效性。
The submarine demonstration is at the beginning of its whole life cycle. In particular, the demonstration of submarine operational performances is the key node in the whole demonstration process, which as a bridge connects military requirements and conceptual alternatives. Hence, the resulting operational performances should both satisfy top military requirements and be feasible in submarine engineering. But the current demonstration methodology has some limitations that lead to two questions. One question is that whether or not the resulting operational performances can satisfy top military requirements optimally. The other is that that whether or not the resulting operational performances would be feasible in practice. The current demonstration methodology can not answer the questions satisfactorily. Therefore, at the latter stage it is possible that some decisions made before would be found false. But at that time adjusting the decisions would be very costly. Hence, it is a very important problem to identify the submarine operational performances based on top military requirements reasonably, and at the same time to keep the resulting operational performances stable.
In order to assure that the resulting operational performances have considerable stability, this dissertation define the concept of dual domain robust optimality, and bring forward a new demonstration pattern for submarine operational performances to avoid some flaws in the traditional pattern. The main contents and achievement of this dissertation are listed as follows:
(1)Aiming at the issue of submarine operational performances demonstration, a methodology of Multi-Expert based requirement-Traceable dual-domain Robust Optimization (METRO) is put forward. METRO emphasizes the traction from top military requirements. That is, the identification and the validation of operational performances are both based on top military requirements. Firstly, it constructs the traceable mapping between top military requirements and operational performances, and the cognitive robustness to this mapping is assured through the information fusion of multi experts' preferences. Then, It constructs the mapping from operational performances to conceptual alternatives, and alternative's robustness is assured through the uncertainty analysis. At last, an optimization process is used to integrate the above elements as a whole in harmony. Summing up, this methodology can resolve the feasibility, optimality, robustness and traceability of the resulting operational performances in a systematic manner.
(2)Aiming at the issue of constructing the traceable mapping between top military requirements and operational performances, a method for the mapping of military requirements based on QFD/ANP and fuzzy integral is proposed. Firstly, based on QFD driven by customer needs and ANP, an integrated operational requirement analysis method is proposed, which can consider the complex relations between military requirements, operational tasks, operational performances, similar equipments, and conceptual alternatives simultaneously, and can handle the information in an uniform and structural manner. Hence, the nicety and consistency of the experts'judgement is improved. Thus, the mapping from top military requirements to operational performances is built. Then, the concept of fuzzy measures is used to describe the relations between the operational performances, and a new algorithm for the calculating of fuzzy measures is developed by the integration of ANP and Influence Matrix, which is suit for the situations without historical data, and is easily understood and executed. With this algorithm, the difficulties in applying fuzzy measures in MCDM are greatly decreased. At last, the military utility model of submarine conceptual alternatives based on Choquet fuzzy integral is established.
(3)In order to assure the judgement about the mapping between between top military requirements and operational performances to be robust, a method of information fusion based on multi-expert multi-format preference and consensus reaching is proposed. Firstly, the methods to uniform multi-format preferences are studied. Especially the method to uniform multi- granularity and multi-semantic linguistic matrices is studied, which proves that there is no information loss and the linguistic comparison matrix will keep its properties after unification. Thus, by these unification methods, an expert would express his real preferences using the familiar format, which would improve the robustness of decisions. Then, a new method to deal with the interactions between the experts'preferences is proposed, which is based on the resemblance degree between the experts'knowledge and between the experts' knowledge comparison matrices, to calculate the 2-additive fuzzy measures to represent the importance of experts. Choquet integral is used as the aggregation operators to obtain group's preference. By this method, experts'power in decision making problem could be identified reasonably, which would be beneficial to obtain sounder group preference and to improve the robustness of decisions. At last, based on the evaluation of the aggregation and the measurement of group consensus degree, group consensus is reached through feedback information.
(4)In order to quantify the influence of uncertainty from submarine sub-systmems, a method for the evaluation of robustness index based on Gaussian Process (GP) surrogate model is proposed. Firstly, the concept of robustness index of submarine conceptual alternatives is defined, and the robustness index of a single alternative can be calculated by Monte Carlo approach. But, calculating the robustness index of many alternatives will lead to a serious issue of calculating efficiency. To resolve this problem, a method for the evaluation of robustness index based on Gaussian Process (GP) surrogate model is proposed, which construct a response surface in the design space to fit the values of robustness index. Through this method, the robustness index value of arbitrary alternative can be evaluated quickly. In the process of GP surrogate modeling, the difficulties arise in the selection of core functions and the identification of hyper-parameters. Hence, this dissertation propose to use mixed core functions, and a new hyper-parameters optimization algorithm based deterministic annealing is developed, which can effectively improve optimization efficiency and results'precision.
(5) Based on the work above, it is proposed to adopt the dual response surface based optimization approach to find the resulting operational performances that is optimal. A multi-objective optimization algorithm based on marginal distribution estimation is applied in the optimization of submarine operational performances. At the end of this dissertation, a example of a multi-task attack submarine is illustrated, which is used to validate the proposed methodology.
为了保证潜艇装备作战使用性能论证所提出的作战使用性能指标的量化要求具备相当的稳定性,本文提出了潜艇装备作战使用性能指标的双域稳健最优性的概念,并针对传统的潜艇装备作战使用性能论证模式存在的问题提出了新的潜艇装备作战使用性能双域稳健优化论证模式。具体来说,本文的主要研究内容和成果包括以下几个方面：
(1)面向潜艇装备作战使用性能论证问题,提出了基于群决策的可追溯双域稳健优化(Multi-Expert based, requirement-Traceable dual-domain Robust Optimization,简称METRO)方法论。METRO方法论强调军事需求的牵引作用,作战使用性能论证是以顶层的军事需求为初始的出发点,同时论证结果的验证也是以对于顶层的军事需求的满足程度为最终的落脚点。首先,通过建立军事需求与作战使用性能之间的双向可追溯映射关系,并通过多专家信息融合的方式保证了在认知域内对于这一双向可追溯映射关系的认识具有相当的稳健性。然后,通过建立计算机化的潜艇装备概念方案设计综合模型来反映作战使用性能与概念方案之间的映射关系,并通过不确定性分析保证在物理域内概念方案的稳健性。最后,通过一个优化过程将上述要素集成为一个有着共同目标的协调一致运作的整体,能够以一种系统化的方式解决最终提出的作战使用性能要求的可行性、最优性、稳健性和可追溯性问题。
(2)针对建立军事需求与作战使用性能的双向可追溯映射关系这一问题,提出了基于QFD/ANP和模糊积分的武器装备军事需求映射技术。首先,提出了一种基于QFD和ANP的武器装备作战需求分析模型,能够综合考虑军事需求、作战任务、作战使用性能、国内外同类装备和装备概念方案之间的复杂关系,同时能够以一种统一的和结构化的方式对其中所包含的信息进行处理,提高了判断的准确性和一致性,实现了从顶层的军事需求到底层的作战使用性能的映射。其次,以模糊测度的概念描述作战使用性能之间的相互关系,并提出了一种基于ANP的模糊测度计算方法,适用于没有历史数据可以利用的情况,并且易于专家的理解和操作,大大降低了模糊测度在实际决策问题中的应用难度。最后,在以上研究基础上建立了基于Choquet积分的潜艇装备概念方案军事效用模型,实现了从底层的作战使用性能到顶层的军事需求的映射。
(3)为了在认知域内确保对于所建立的军事需求与作战使用性能指标的双向可追溯映射关系的判断具有稳健性,提出了基于多种形式偏好信息的多专家信息融合及共识技术。首先,研究了多种形式偏好信息的一致化方法,重点研究了多粒度多语义语言判断矩阵的一致化方法,该方法能够保证在任意语言评价集之间的信息无损的转换。这使得专家能够以自己熟悉的形式给出判断信息,有利于获取专家的真实偏好,可以提升决策结果的稳健性。其次,在专家偏好信息一致化的基础上,针对专家偏好可能存在关联关系的问题,提出了一种基于主客观信息的综合赋权方法,能够根据专家知识结构之间的相似度和专家偏好信息之间的相似度,确定专家的重要程度(用2-可加模糊测度的概念对其进行表示),并使用Choquet积分对专家偏好信息进行融合。通过合理确定专家的决策权力,能够获取真实反应群体意见的结果,同样有利于提升决策结果的稳健性。最后,通过对信息融合过程的评价以及对群体共识水平的测度,以反馈的方式引导群体达成共识。
(4)针对在物理域内将备选分系统的不确定因素对于潜艇装备作战使用性能的影响程度进行量化的问题,提出了基于高斯过程元模型的潜艇装备概念方案稳健性评估技术。首先,定义了潜艇装备概念方案的稳健性指标,并基于蒙特卡洛方法对单个概念方案的稳健性指标进行评估。然后,为了解决大量概念方案的稳健性指标评估所带来的严重计算效率问题,提出了基于高斯过程元模型的稳健性评估技术,利用高斯过程元模型构建设计空间中概念方案的稳健性指标值的响应面,能够快速对任意方案的稳健性指标进行评估。针对高斯过程建模中关键的相关函数选择和超参数优化问题,提出了使用混合核函数的策略和基于确定性退火算法的超参数优化方法,与现有的超参数优化算法相比,优化效率和结果精度都有显著提高。
(5)在以上研究基础上,采用基于双响应面的稳健优化策略,并将于边缘分布估计的多目标优化算法(MOMDA)应用于潜艇装备作战使用性能优化问题。最后,以一种多用途攻击型潜艇装备作战使用性能论证为例,应用所提出的方法论和关键技术解决问题,验证了方法的可行性和有效性。
The submarine demonstration is at the beginning of its whole life cycle. In particular, the demonstration of submarine operational performances is the key node in the whole demonstration process, which as a bridge connects military requirements and conceptual alternatives. Hence, the resulting operational performances should both satisfy top military requirements and be feasible in submarine engineering. But the current demonstration methodology has some limitations that lead to two questions. One question is that whether or not the resulting operational performances can satisfy top military requirements optimally. The other is that that whether or not the resulting operational performances would be feasible in practice. The current demonstration methodology can not answer the questions satisfactorily. Therefore, at the latter stage it is possible that some decisions made before would be found false. But at that time adjusting the decisions would be very costly. Hence, it is a very important problem to identify the submarine operational performances based on top military requirements reasonably, and at the same time to keep the resulting operational performances stable.
In order to assure that the resulting operational performances have considerable stability, this dissertation define the concept of dual domain robust optimality, and bring forward a new demonstration pattern for submarine operational performances to avoid some flaws in the traditional pattern. The main contents and achievement of this dissertation are listed as follows:
(1)Aiming at the issue of submarine operational performances demonstration, a methodology of Multi-Expert based requirement-Traceable dual-domain Robust Optimization (METRO) is put forward. METRO emphasizes the traction from top military requirements. That is, the identification and the validation of operational performances are both based on top military requirements. Firstly, it constructs the traceable mapping between top military requirements and operational performances, and the cognitive robustness to this mapping is assured through the information fusion of multi experts' preferences. Then, It constructs the mapping from operational performances to conceptual alternatives, and alternative's robustness is assured through the uncertainty analysis. At last, an optimization process is used to integrate the above elements as a whole in harmony. Summing up, this methodology can resolve the feasibility, optimality, robustness and traceability of the resulting operational performances in a systematic manner.
(2)Aiming at the issue of constructing the traceable mapping between top military requirements and operational performances, a method for the mapping of military requirements based on QFD/ANP and fuzzy integral is proposed. Firstly, based on QFD driven by customer needs and ANP, an integrated operational requirement analysis method is proposed, which can consider the complex relations between military requirements, operational tasks, operational performances, similar equipments, and conceptual alternatives simultaneously, and can handle the information in an uniform and structural manner. Hence, the nicety and consistency of the experts'judgement is improved. Thus, the mapping from top military requirements to operational performances is built. Then, the concept of fuzzy measures is used to describe the relations between the operational performances, and a new algorithm for the calculating of fuzzy measures is developed by the integration of ANP and Influence Matrix, which is suit for the situations without historical data, and is easily understood and executed. With this algorithm, the difficulties in applying fuzzy measures in MCDM are greatly decreased. At last, the military utility model of submarine conceptual alternatives based on Choquet fuzzy integral is established.
(3)In order to assure the judgement about the mapping between between top military requirements and operational performances to be robust, a method of information fusion based on multi-expert multi-format preference and consensus reaching is proposed. Firstly, the methods to uniform multi-format preferences are studied. Especially the method to uniform multi- granularity and multi-semantic linguistic matrices is studied, which proves that there is no information loss and the linguistic comparison matrix will keep its properties after unification. Thus, by these unification methods, an expert would express his real preferences using the familiar format, which would improve the robustness of decisions. Then, a new method to deal with the interactions between the experts'preferences is proposed, which is based on the resemblance degree between the experts'knowledge and between the experts' knowledge comparison matrices, to calculate the 2-additive fuzzy measures to represent the importance of experts. Choquet integral is used as the aggregation operators to obtain group's preference. By this method, experts'power in decision making problem could be identified reasonably, which would be beneficial to obtain sounder group preference and to improve the robustness of decisions. At last, based on the evaluation of the aggregation and the measurement of group consensus degree, group consensus is reached through feedback information.
(4)In order to quantify the influence of uncertainty from submarine sub-systmems, a method for the evaluation of robustness index based on Gaussian Process (GP) surrogate model is proposed. Firstly, the concept of robustness index of submarine conceptual alternatives is defined, and the robustness index of a single alternative can be calculated by Monte Carlo approach. But, calculating the robustness index of many alternatives will lead to a serious issue of calculating efficiency. To resolve this problem, a method for the evaluation of robustness index based on Gaussian Process (GP) surrogate model is proposed, which construct a response surface in the design space to fit the values of robustness index. Through this method, the robustness index value of arbitrary alternative can be evaluated quickly. In the process of GP surrogate modeling, the difficulties arise in the selection of core functions and the identification of hyper-parameters. Hence, this dissertation propose to use mixed core functions, and a new hyper-parameters optimization algorithm based deterministic annealing is developed, which can effectively improve optimization efficiency and results'precision.
(5) Based on the work above, it is proposed to adopt the dual response surface based optimization approach to find the resulting operational performances that is optimal. A multi-objective optimization algorithm based on marginal distribution estimation is applied in the optimization of submarine operational performances. At the end of this dissertation, a example of a multi-task attack submarine is illustrated, which is used to validate the proposed methodology.
引文
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