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 concep

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 concep