We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Particle Swarm Optimization Combined with Inertia-Free Velocity and Direction Search.
- Authors
Miao, Kun; Feng, Qian; Kuang, Wei; Taheri, Javid
- Abstract
The particle swarm optimization algorithm (PSO) is a widely used swarm-based natural inspired optimization algorithm. However, it suffers search stagnation from being trapped into a sub-optimal solution in an optimization problem. This paper proposes a novel hybrid algorithm (SDPSO) to improve its performance on local searches. The algorithm merges two strategies, the static exploitation (SE, a velocity updating strategy considering inertia-free velocity), and the direction search (DS) of Rosenbrock method, into the original PSO. With this hybrid, on the one hand, extensive exploration is still maintained by PSO; on the other hand, the SE is responsible for locating a small region, and then the DS further intensifies the search. The SDPSO algorithm was implemented and tested on unconstrained benchmark problems (CEC2014) and some constrained engineering design problems. The performance of SDPSO is compared with that of other optimization algorithms, and the results show that SDPSO has a competitive performance.
- Subjects
PARTICLE swarm optimization; MATHEMATICAL optimization; VELOCITY; GLOBAL optimization; ENGINEERING design
- Publication
Electronics (2079-9292), 2021, Vol 10, Issue 5, p597
- ISSN
2079-9292
- Publication type
Article
- DOI
10.3390/electronics10050597