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首页> 外文期刊>Mathematical Problems in Engineering: Theory, Methods and Applications >A Design-Task-Oriented Model Assignment Method in Model-Based System Engineering
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A Design-Task-Oriented Model Assignment Method in Model-Based System Engineering

机译:基于模型的系统工程中的设计 - 面向设计的模型分配方法

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In model-based system engineering (MBSE), reuse of existing models in the development of a new system can be advantageous. Automatic assignment of existing models to each design task within a design task set has been proven to be feasible. However, while several studies have discussed the significance of models in MBSE and methodologies for models reuse, solving the model reusability problem through a model assignment method has not been discussed. Additionally, a significant challenge in model assignment is to address the conflict between the maximization of the model value summations, which are yielded by assigning the models to a design task set, and the minimization of the execution cycle of the task set. This study (a) proposes a design-task-oriented model assignment method that establishes a multiobjective model, based on a model assignment integration framework, and (b) designs a differential-evolution-combined adaptive nondominated sorting genetic algorithm-II to provide an optimal tradeoff between maximizing the total model values and minimizing the execution cycle of the task set. By comparing the performance of the algorithm in resolving the assignment of models to a design task set with those of two conventional algorithms in a phased-array radar development project, the algorithm’s performance and promotion of system development are verified to be superior. The new method can be applied for developing model scheduling software for MBSE-compliant product development projects to improve using effects of the models and development cycle.
机译:在基于模型的系统工程(MBSE)中,在新系统的开发中重用现有模型可能是有利的。已经证明,已经证明了在设计任务集中的每个设计任务中对现有模型的自动分配是可行的。然而,虽然若干研究已经讨论了MBSE和模型重用的方法中模型的重要性,但尚未讨论通过模型分配方法解决模型可重用性问题。此外,模型分配中的重大挑战是通过将模型分配给设计任务集来解决模型值求和的最大化之间的冲突,以及任务集的执行周期的最小化最小化。本研究(a)提出了一种设计任务为导向的模型分配方法,该模型分配方法基于模型分配集成框架建立多目标模型,(B)设计差分交换组合的自适应Nondominated分类遗传算法-II以提供一个最大化总模型值和最小化任务集执行周期之间的最佳权衡。通过比较算法在分辨阵列雷达开发项目中的两个传统算法中分辨模型的分配到设计任务集的性能,算法的性能和促销系统开发的验证是优越的。新方法可用于开发用于开发MBSE标准的产品开发项目的模型调度软件,以改善模型和开发周期的效果。

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