Porcellio scaber algorithm (PSA) for solving constrained optimization problems
This provides a new bio-inspired optimization method for researchers and practitioners tackling constrained optimization problems, though it appears incremental as an extension of an existing algorithm.
The authors extended the bio-inspired Porcellio Scaber Algorithm (PSA) to solve constrained optimization problems, including mixed discrete-continuous nonlinear cases, and found it outperformed many existing methods in benchmark tests.
In this paper, we extend a bio-inspired algorithm called the porcellio scaber algorithm (PSA) to solve constrained optimization problems, including a constrained mixed discrete-continuous nonlinear optimization problem. Our extensive experiment results based on benchmark optimization problems show that the PSA has a better performance than many existing methods or algorithms. The results indicate that the PSA is a promising algorithm for constrained optimization.