GENETIC ALGORITHMS-BASED METHODOLOGIES FOR DESIGN OPTIMIZATION OF TRUSSES

Design optimization of trusses consists of arriving at optimum topolog y, configuration, and sizes of cross-sectional parameters, when weight of the truss is minimum, satisfying a set of specified constraints. G enetic algorithms-based methods provide ideal techniques for modeling many practical considerations, which make the optimal solution constru ctible. Two improved methods for size and configuration optimization a nd topology optimization are presented in this paper. The first one is a two-phase method, which in addition to arriving at better solutions compared to those obtained using earlier methods, also improves the c omputational efficiency. The second method, based on a variable string length genetic algorithm (VGA), addresses the topology optimization p roblem, taking into account a number of practical issues. Classical pr oblems from literature are solved and the results are compared. Featur es of the proposed method which help in modeling and application to op timal design of large truss structures, are demonstrated by solving a problem of a microwave antenna tower.