an optimized swarm intelligence algorithm based on the mass defence of bees

Swarm intelligence is a modern optimization technique and one of the most efficient techniques for solving optimization problems. their main inspiration is the cooperative behavior of animals within specific communities. in swarm intelligence algorithms, agents work together and the collective behavior of all agent causes converge at a point close to the global optimal solution. in this paper, we model the behavior of bees in defending the hive against invading bees to provide a new optimization algorithm. in the proposed algorithm, the coordinated performance of bees in identifying the invader creating a circle around the invading bee and generating heat during the siege of the invading bee and also the heat emitted from each bee are modeled. the simulation results of the proposed algorithm show a successful competitive behavior in achieving the global optimum in comparison with the firefly, ant colony, artificial bee colony, whale and grey wolf algorithms.