Objective:

In this paper, a continuous genetic algorithm (CGA) for the optimal design of a closed-coil helical spring is proposed.

Methodology:

The solution methodology uses the minimization of the total spring volume as objective function, considering the wire diameter, mean diameter and number of active coils as main variables. As set of constraints, the technical and physical requirements for the correct and safe design of the aforementioned element are implemented. A CGA is employed as a solution method, and, as comparison methods, different optimization algorithms were used, which were employed in the specialized literature for solving the problem addressed in this study.

Results:

The results obtained show that the CGA achieved the minimum value of volume, 1.5% less than the best reported technique, with a processing time lower than 1 s, which proves that the proposed methodology obtains the best results in terms of solution quality and processing time.

Conclusions:

The simulation results show that the CGA obtains the best solution in comparison with the other techniques, at a low computational cost and providing a solution that meets the physical and technical constraints of the design.