An Optimization Algorithm using Orthogonal Arrays in Discrete Design Space for Structures

Abstract

Structural optimization has been carried out in continuous or discrete design space. Methods for discrete design such as genetic algorithms are extremely expensive in computational cost. In this research, an iterative optimization algorithm using orthogonal arrays is proposed for design in discrete space. An orthogonal array is selected on a discrete design space and levels are chosen from candidate values. Matrix experiments with the orthogonal array are conducted. A characteristic function is defined to consider the constraint feasibility. A new design in a certain iteration is determined from analysis of means (ANOM) with the characteristic function. An orthogonal array is defined around the new values and matrix experiments are conducted again with the new orthogonal array. The final optimum design is found from the iterative process. Various structural problems are solved to show the validity of the proposed method. The results are compared with those from a genetic algorithm and discussed.