A Genetic Algorithm Based Multi-step Design Optimization of a Machine Structure for Minimum Weight and Compliance

摘要

This paper presents a multi-step design optimization method for machine structures using a genetic algorithm with dynamic penalty function. The first step is the sectional topology optimization, which is to determine the best cross-section topology for structural members of a machine tool. The second step is static design optimization, in which the weight and the static compliance response are minimized under some dimensional and safety constraints. A set of good design solutions, which have relatively higher fitness, is extracted by using G.A. The third step is dynamic design optimization, where the best design solution, that the highest fitness for minimum weight, static compliance, and dynamic compliance, is determined from the good design solution set of the second design stage. The proposed design method was examined on the 10-bar truss problem of topology and sizing optimization. And the results showed that our solution is better than or almost equal to the best one of the previous researches. Furthermore, we applied this method to the topology and sizing optimization of a crossbeam structure for a gantry typed machine tool. The example demonstrated the feasibility of the suggested design optimization method.