A Game Theoretic Based Scheme for Multidisciplinary Optimization with Uncertainty
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.
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 http://dx.doi.org/10.1115/IMECE2004-59742
2004 ASME International Mechanical Engineering Congress and Exposition (2004: Nov. 13-19, Anaheim, CA)
Mechanical and Aerospace Engineering
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
Article - Conference proceedings
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