Evaluation of new methods of intelligent optimization in truss structures

Achieving the best results for an operation while meeting certain constraints is called optimization. In this research, we have tried to introduce an algorithm that achieves thebest result of the objective function in the fastest possible time by comparing the speed and accuracy of new intelligent optimization methods as the most appropriate algorithm. To do this, the cross-sectional optimization and weight of the ۱۰-member truss structure under stress constraints were investigated in two stages, in the first stage using three types of cuckoo optimization algorithms, light worm and particle swarm. The results show that the evolution of the firewall algorithm is more efficient than the other two algorithms. Also, the particle swarm algorithm has the highest speed. Among all three algorithms, the firewall algorithm can be considered the most optimal algorithm for time and accuracy. In the second stage, using three types of ant colony algorithms, colonial competition and genetic algorithm, the speed and accuracy of the mentioned methods in optimizing structures were investigated. The colonial competition algorithm was more efficient and better than the other two algorithms.

Keywords:

Optimization of structures , algorithms , intelligentization in structures , truss structures