Experimental Comparison of Constraint Handling Schemes in Particle Swarm Optimization
Abstract
Nature-inspired optimization algorithms have been designed for unconstrained problems. However, real-world optimization problems usually deal with a lot of limitations, either boundary of design variables, or equality/inequality constraints. Therefore, an extensive number of efforts have been made to make these limitations understandable for the optimization algorithms. Here, a more important fact is that those constraint handling approaches affect the algorithms' performances considerably. In this study, some of the well-known strategies are incorporated into particle swarm optimization algorithms (PSO). The performance of the PSO algorithm is examined through several benchmarks, constrained problems, and the results discussed comprehensively.
Publication Title
Constraint Handling in Metaheuristics and Applications
Recommended Citation
Rostamian, M., Kashani, A., Camp, C., & Gandomi, A. (2021). Experimental Comparison of Constraint Handling Schemes in Particle Swarm Optimization. Constraint Handling in Metaheuristics and Applications, 81-99. https://doi.org/10.1007/978-981-33-6710-4_4
