Hierarchical parallel processing for design optimization - a case study

The optimization methods can be applied to design large scale mechanical systems. One popular method for increasing the efficiency of large scale design optimization problem is a hierarchical decomposition of the problem into a number of sub problems each with its own objective function, constraints, and design variables. Then each and every sub problem is optimized by using a powerful tool known as genetic algorithm, to get required optimum solutions. The solutions obtained from sub problems are used to get the required global optimum solution of a large and complex design problem. A well known speed reducer is considered as an example to illustrate the application of the above parallel processing method. Speed reducer includes gear, pinion, two shafts, four bearings enclosed in housing. The design objective is to minimize the overall volume, where 7 variables and 25 constraints are considered. (C) 2017 Elsevier Ltd. All rights reserved.