Discrete parameter-nonlinear constrained optimisation of a gear train using genetic algorithms. (24th June 2005)

• Record Type: Journal Article
• Authors: Dolen, M.; Kaplan, H.; Seireg, A.
• Is Part Of: International journal of computer applications technology. Volume 24:Number 2(2005)
• Page Start: 110
• Page End: 121
• Publication Date: 2005-06-24
• Subjects: genetic algorithms -- discrete design optimisation -- penalty function -- integer programming -- multi stage gear design -- nonlinear programming -- gear train optimisation -- optimal design -- gearbox size -- geometric constraints; Technology -- Data processing -- Periodicals; 620.00285
• Languages: English
• ISSNs: 0952-8091

Abstract

This paper investigates the optimal design of a four-stage gear train using genetic algorithms. Five different genetic encoding schemes, which incorporate various heuristic search techniques, are proposed to deal with the most critical constraints of the problem. The fitness criterion used by all genetic algorithms includes a merit function for minimising the size of the gearbox. The results show improvement in the design merit over previous approaches without reliance on the designer's interaction to avoid geometric constraint violations and facilitate the convergence.