Size optimization of planar truss systems using the modified salp swarm algorithm

ABSTRACT

This work evaluates the performance of the salp swarm algorithm (SSA) for truss system optimization problems and presents a novel method called the modified salp swarm algorithm (MSSA). Five truss structures, previously optimized by metaheuristics and containing discrete and continuous variables, were used for the evaluations. Size and size–shape optimization types were considered. Although the SSA performs poorly and has convergence issues in initial random solutions, it reaches comparable solutions to previously published results, particularly in continuous problems. In contrast, the MSSA achieves the best solutions for discrete problems and is relatively close to the best results in the reference literature on continuous problems. Moreover, the MSSA convergence curves exhibit a modest increase in convergence rates, especially for discrete problems. It is envisaged that the findings will contribute to improving solution performance, convergence speed and security for future real-world applications.

KEYWORDS:

• Structural optimization
• metaheuristic techniques
• swarm intelligence
• truss systems
• salp swarm algorithm

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.