Abstract

 A particular intelligent behavior of a honey bee swarm, foraging behavior, is considered and a new artificial bee colony algorithm simulating this behavior of real honey bees for solving multidimensional and multimodal optimization problems. A new optimization algorithm based on the intelligent behavior of honey bee swarm has been described. The proposed algorithm can be used for solving Traveling salesman problem and other applications. The proposed research work combines the energy awareness and efficiency with the Swarm Intelligence (SI) optimization to determine on-demand optimal path between a certain source-destination pair. Bee Colony Optimization (BCO) model is a new general purpose Swarm Intelligence optimization technique based on efficient labor employment and efficient energy consumption through a multi-agent distributed model. BCO model has adopted mainly two natural behaviors from the social bees’ life: The mating process behavior and the foraging process behavior.

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