Nature Inspired Optimization Technique : Bacterial Foraging Algorithm
In this era of modernization, deregulation and competition the scenario of the optimization techniques is being evolved dramatically towards the functional mimicry of nature. There are many nature-inspired optimization algorithms such as PSO, Ant Colony, Genetic Algorithm, Evolutionary Techniques etc. Recently Bacterial foraging Optimization Algorithm has attracted a lot of attention as a high-performance optimizer. In 2002, K. M. Passino proposed Bacterial Foraging Optimization Algorithm for distributed optimization and control. One of the major driving forces of BFOA is the chemotactic movement of a virtual bacterium that models a trial solution of the optimization problem. The underlying biology behind the foraging strategy of E.coli is emulated in an extraordinary manner and used as a simple optimization algorithm. This paper presents the BFOA for global optimization.