多数非劣解集合からの設計支援手法の開発

ジェットエンジン最適化を通して

抄録

This paper proposes a new design support approach, which efficiently utilizes the information of many non-dominated solutions obtained from evolutionary multi-criterion optimization (EMO). The proposed approach consists of four mechanisms: grouping (clustering), reducing the number of candidates (selecting the representative solutions), dimensionality reduction, and estimation.

Non-dominated solutions can be regarded as a beneficial subspace in whole search space, which have the feature of being non-inferior to other solutions. Therefore, we think the proposed approach can be used to estimate the characteristics of a problem through the interaction with the designer.

In this paper, we examine the characteristics and effectiveness of the proposed approach through computational experiments on a design problem of a counter rotating axial fan turbojet engine. A counter rotating axial fan turbojet engine with two spools is chosen for the design target of the present study. We handle this task as a seven-objective design problem.