A Game Theoretic Based Scheme for Multidisciplinary Optimization with Uncertainty
Abstract
A game theoretic based scheme is considered in this study for multidisciplinary design optimization under uncertain conditions. The methodology developed is illustrated by considering the example of an internal combustion (IC) engine. Various game protocols are used to model the optimization process and the results obtained are compared with each other. A genetic algorithm (GA) is used as an optimization and constraining tool. Convergence, constraint handling and processing time are considered to evaluate the efficacy of the methodology developed.
Recommended Citation
A. Gupta and K. Krishnamurthy, "A Game Theoretic Based Scheme for Multidisciplinary Optimization with Uncertainty," Proceedings of the 2004 ASME International Mechanical Engineering Congress and Exposition (2004, Anaheim, CA), vol. 73, no. 1 PART A, pp. 645 - 652, American Society of Mechanical Engineers (ASME), Nov 2004.
The definitive version is available at https://doi.org/10.1115/IMECE2004-59742
Meeting Name
2004 ASME International Mechanical Engineering Congress and Exposition (2004: Nov. 13-19, Anaheim, CA)
Department(s)
Mechanical and Aerospace Engineering
Sponsor(s)
ASME, Dynamic Systems and Control Division
Keywords and Phrases
Constraint theory; Genetic algorithms; Optimization; Probability; Product development; Risk assessment; Sensitivity analysis; Uncertain systems; Engineering system design; Non-cooperative optimization; Robust design; Uncertainty in design; Game theory; Game theory; Genetic algorithms
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2004 American Society of Mechanical Engineers (ASME), All rights reserved.
Publication Date
01 Nov 2004
