Abstract
In this paper, we investigate the issue of convergence in multi-objective optimisation problems developed for vehicle analyses when using a Multi-Objective Genetic Algorithm (MOGA) to determine the set of Pareto optimal automobile configurations. Additionally, given a Pareto set for a multi-objective problem, the mapping between the performance and design space is studied to determine new automobile design configurations for a given set of performance specifications. The advantage of this study is that the automobile's design information is obtained without having to repeat system analyses. The tools developed in this paper are applied both to a simple multi-objective optimisation problem to illustrate the methodology and to a preliminary vehicle design framework to develop a Technical Feasibility Model (TFM) for use in the early stages of automobile design.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Vehicle Systems Modelling and Testing
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
