MULTIOBJECTIVE COLLABORATIVE OPTIMIZATION

This investigation focuses on the development of modifications to the Collaborative Optimization (CO) approach to multidisciplinary systems design, that will provide solution capabilities for multiobjective pro blems. The primary goal of this paper is to provide a comprehensive ov erview and development of mathematically rigorous optimization strateg ies for MultiObjective Collaborative Optimization (MOCO). Collaborativ e Optimization strategies provide design optimization capabilities to discipline designers within a multidisciplinary design environment. To date these CO strategies have primarily been applied to system design problems which have a single objective function. Recent investigation s involving multidisciplinary design simulators have reported success in applying CO to multiobjective system design problems. In this resea rch three MultiObjective Collaborative Optimization (MOCO) strategies are developed, reviewed and implemented in a comparative study. The go al of this effort is to provide an in depth comparison of different MO CO strategies available to system designers. Each of the three strateg ies makes use of parameter sensitivities within multilevel solution st rategies. in implementation studies, each of the three MOCO strategies is effective in solving a multiobjective multidisciplinary systems de sign problem. Results indicate that these MOCO strategies require an a ccurate estimation of parameter sensitivities for successful implement ation. In each of the three MOCO strategies these parameter sensitivit ies are obtained using post-optimality analysis techniques.