Application of Bee Colony Optimization (BCO) in NP-Hard Problems

This report presents the first stage of an ongoing research which is the problem
solving of highly complex tasks using Bee-Inspired algorithms. Bee-Inspired
algorithms are partially referring to the nature of bee swarm behaviour. Bee
swarm behaviour characterized by autonomy and distributed functioning and selforganizing.
Nowadays, lots algorithms under the field of Swann Intelligent have
been used to solve complex problem. Various Artificial Intelligence systems have
been developed based on plenty of researches and studies done on the behaviour
of social insects. Bee-Inspired algorithms were presumed to bring the new
direction in the field of Swann Intelligence.
The primary goal of this research is to prove the efficiency of collective bee
intelligence in solving problems characterized by uncertainty. P-Median problem
will be used as the main case study in implementing one of the Bee-Inspired
algorithms to prove, illustrate example and show the characteristics of the
selected concept