Improved Local Search in Artificial Bee Colony using Golden Section Search
This is an incremental improvement for optimization in engineering design, potentially aiding in solving real-life problems more effectively.
The authors tackled the problem of local optima in the Artificial Bee Colony algorithm by incorporating a golden section search mechanism, resulting in improved global convergence and performance on unconstrained engineering design problems.
Artificial bee colony (ABC), an optimization algorithm is a recent addition to the family of population based search algorithm. ABC has taken its inspiration from the collective intelligent foraging behavior of honey bees. In this study we have incorporated golden section search mechanism in the structure of basic ABC to improve the global convergence and prevent to stick on a local solution. The proposed variant is termed as ILS-ABC. Comparative numerical results with the state-of-art algorithms show the performance of the proposal when applied to the set of unconstrained engineering design problems. The simulated results show that the proposed variant can be successfully applied to solve real life problems.