Now showing items 1-3 of 3
A clustering particle swarm optimizer for dynamic optimization.
In the real world, many applications are nonstationary optimization problems. This requires that optimization algorithms need to not only find the global optimal solution but also track the trajectory of the changing global ...
Adaptive learning particle swarm optimizer-II for global optimization.
This paper presents an updated version of the adaptive learning particle swarm optimizer (ALPSO), we call it ALPSO-II. In order to improve the performance of ALPSO on multi-modal problems, we introduce several new major ...
A memetic particle swarm optimisation algorithm for dynamic multi-modal optimisation problems.
(Taylor & Francis, 2012)
Many real-world optimisation problems are both dynamic and multi-modal, which require an optimisation algorithm not only to find as many optima under a specific environment as possible, but also to track their moving ...