The Optimization Design of I-Beam Based on Multi-Objective Cellular Genetic Algorithm

TLDR: The results show that multi-objective cellular genetic algorithm has more advantages than the traditional multi- objective evolutionary algorithms in solving this kind of multi-Objective problems, no matter in uniformity or expansibility of best solutions.

Abstract: Multi-objective cellular genetic algorithm is obviously superior to the traditional multi-objective evolutionary algorithms in terms of testing performance of algorithm. However, the algorithm still needs to be used in practical engineering problems. In consideration of the above, this paper tries to apply the multi-objective cellular genetic algorithm to solve the problem of design of I-beam. Finally, the results show that multi-objective cellular genetic algorithm has more advantages than the traditional multi-objective evolutionary algorithms in solving this kind of multi-objective problems, no matter in uniformity or expansibility of best solutions.