Search

In this paper, general strategies are presented by which a multi-domain, multi-objective, mechanism-based optimization problem may be efficiently formulated and solved by means of a genetic algorithm. These strategies include integration of traditional precision position techniques with genetic optimization, efficient selection of design variables and search bounds, and a nested optimization structure. A case study illustrating these methods is presented in which a hydraulic rescue spreader is simultaneously optimized for four objectives relating to structural efficiency and kinematic behavior. The solution obtained is shown to be equal or superior to a comparable commercially available device with respect to all four objectives. [ABSTRACT FROM AUTHOR]