AI Summary & Key Takeaways
AI InsightComparative results show that the proposed model increased the quality of the solutions and early convergence speed while protecting the speedup gain.
📌 3 Key Takeaways
Abstract
Artificial Bee Colony algorithm inspired by the foraging behavior of real honey bees is one of the most popular swarm intelligence based optimization techniques. Like other population based evolutionary computation approaches, Artificial Bee Colony algorithm is intrinsically suitable for distributed architectures. However, determining which food source should be chosen to distribute between subcolonies and communication topology applied still remain as an important problem for parallel implementations. In this study, a new schema for increasing the quality of the distributed source by changing best solution is presented. The proposed model is adapted to ring migration topology and its effectivenes is compared with conventional ring based topology in which best food sources in each subpopulation are distributed and the original sequential counterpart. Comparative results show that the proposed model increased the quality of the solutions and early convergence speed while protecting the speedup gain.