Multidisciplinary Design Optimization(MDO) method that considers principles in various fields affecting big scale structure and system design at the same time is used. Because most variables are connected many engineering phenomena under the classic optimized design method(all-in-one design approach), it is hard to judge the meaning of final design solution obtained, and there are cases where all variables converge before reaching the optimal design value in large-scale design problems with many variables. Collaborative Optimization (CO) method, the most advanced MDO approach, is used to efficiently solve these optimum problems, to efficiently analyze design problems involving numerous design variables and constraints and in which various engineering phenomena occur. However, the application of the MDO problem to CO introduces a number of numerical problems by destroying the numerical properties of the original optimal design problem. Therefore, this study researches one solution by listing the problems of CO after organizing various approaches of MDO.

Abstract
1. 서 론
2. MDO 기법들의 비교
    2.1 Multidisciplinary Feasible(MDF) Method
    2.2 Individual Discipline Feasible(IDF) Method
    2.3 CO(Collaborative Optimization)
3. Penalty Function Method를 통한 CO의수렴성 개선
4. 수치예제
    4.1 CO의 문제점
    4.2 Penalty Function Method를 통한 CO의수렴성 개선
5. 결 론
후 기
References

• 박창규(Member, School of Mechanical & Automotive Engineering, Gwangju University) | Chang-Kyu Park Corresponding author