A tri-objective truss design optimization using a Multi-objective Craziness based Particle Swarm Optimization

Resumo

Recently there has been a growing interest in evolutionary multi-objective optimization algorithms
due to its applicability in problems from several fields, especially those of applied engineering and mathematics.
In this context, there are many of algorithms applied to these types of problems, such as differential evolution,

genetic algorithms, particle swarm, among others. This paper deals with a multi-objetive sizing, discrete or con-
tinuous, strucutural optimization problem with respect to: i) the minimization of the mass of truss structures; ii)

the maximization of the first natural frequency of vibration and iii) the minimization of the maximum displace-
ment, considering stress constraints. A multi-objective particle swarm algorithm called Multi-objective Craziness

based Particle Swarm Optimization (MOCRPSO) is the search algorithm adopted here and an Adaptive Penal-
ization Method (APM), which has been successfully applied to solving mono-objective optimization problems, is

used to handle the constraints. Some computational experiments are analyzed, presenting very interesting results
providing pareto fronts between the objectives.