In model-based system engineering (MBSE), reuse of existing models in the development of a new system can be advantageous.\nAutomatic assignment of existing models to each design task within a design task set has been proven to be feasible. However,\nwhile several studies have discussed the significance of models in MBSE and methodologies for models reuse, solving the model\nreusability problem through a model assignment method has not been discussed. Additionally, a significant challenge in model\nassignment is to address the conflict between the maximization of the model value summations, which are yielded by assigning the\nmodels to a design task set, and the minimization of the execution cycle of the task set. This study (a) proposes a design-taskoriented\nmodel assignment method that establishes a multiobjective model, based on a model assignment integration framework,\nand (b) designs a differential-evolution-combined adaptive nondominated sorting genetic algorithm-II to provide an optimal\ntradeoff between maximizing the total model values and minimizing the execution cycle of the task set. By comparing the\nperformance of the algorithm in resolving the assignment of models to a design task set with those of two conventional algorithms\nin a phased-array radar development project, the algorithmâ??s performance and promotion of system development are verified to\nbe superior.The new method can be applied for developing model scheduling software for MBSE-compliant product development\nprojects to improve using effects of the models and development cycle.
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