Βιομίμηση της αναζήτησης τροφής από το βακτήριο Escherichia Coli και εφαρμογές βελτιστοποίησης
Τσίγκρηλας, Θεόδωρος Β.
During the last decade Bacterial Foraging Optimization Algorithm - BFOA, has been accepted by researchers as a high interest evolutionary optimization algorithm due to the effectiveness in solving optimization problems in various application domains of real world. One of the major driving forces in BFOA is the movement simulation of virtual bacteria, where the model gives on each bacterium a test solution of the optimization problem. During reproduction, the least healthier bacteria (with a lower accumulated value of the objective function in one chemotactic lifetime) die and the other healthier bacteria each split into two, which then starts exploring the search place from the same location resulting in rapid convergence of the bacterial population near optima (local / global). This phenomenon is directly proportional to the mechanism selection in classical evolutionary algorithms. Considering many previous works in this paper we study the social foraging in nature, while the underlying biology behind the foraging strategy of E. coli bacterium is simulated with an excellent manner. It is also used as a new optimization algorithm and attributed to pseudocode and program. We examine experimentally twelve mathematical functions. We conclude with the prospects of BFOA algorithm and a description of the most important applications of BFOA today.