Optimizing the design of a hydrostatic thrust bearing by applying genetic algorithms

Abstract

This paper considers optimizing the design of a hydro­ static thrust bearing by applying genetic algorithms ((7,4s). This is a practical design problem, and the ob­ jective is (i) to confirm that GAs can be successfully applied as an optimization tool in complex engineering design problems,and (it) that the mutation operator in a simple GA can serve as an extremely powerful tool in locating the global optima in the search space in a complicated optimization problem. The optimization criterion involves minimizing the to­ tal power loss to the bearing (U), which is the sum of the pumping energy (Ep) and the frictional loss (Ey). The problem has three design variables and four con­ straints, thus making it a complex optimization prob­ lem irrespective of the optimizing algorithm employed. The problem was earlier solved by the random search technique (rst). GAs are search algorithms based on the mechanics of natural selection and natural genet­ ics. For information on GAs readers are requested to refer [l]. The objective function to be optimized is given by U = E y + E p (1)