Bee Colony Optimization
A. Vinotha Vasuki · 2020
The study of bird and insect behavior has led to the development of swarm intelligence techniques for solving optimization problems. The collective intelligence of a swarm of agents has proved to be very powerful in solving design problems that have been found to be intractable by classical algorithms. The bee colony optimization (BCO) algorithm has been developed from the social interactions and natural foraging behavior of honey bees. The foraging behavior of honey bees has led to the development of the BCO, artificial bee colony optimization, and the bees algorithm. The mating and breeding behavior of honey bees has motivated the development of marriage in honey bees optimization, fast marriage in honey bees optimization, and honey bees mating optimization. The algorithm combines exploitation of the local neighborhood as well as exploration of the search space to find the global optimum.