bacterialforagingoptimization(BFO) is a recently developed nature-inspired optimizationalgorithm,which is based on the foraging behavior of *** ***,BFO possesses a poor convergence behavior over complex optimizatio...
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bacterialforagingoptimization(BFO) is a recently developed nature-inspired optimizationalgorithm,which is based on the foraging behavior of *** ***,BFO possesses a poor convergence behavior over complex optimization problems as compared to other nature-inspired optimization techniques like Genetic algorithm(GA) and Particle Swarm optimization(PSO).This paper first analyzes how the run-length unit parameter controls the exploration and exploitation ability of BFO,and then presents a variation on the original BFO algorithm,called the self-adaptive bacterialforagingoptimization(SA-BFO),employing the adaptive search strategy to significantly improve the performance of the original *** is achieved by enabling SA-BFO to adjust the run-length unit parameter dynamically during evolution to balance the exploration/exploitation *** of SA-BFO on several benchmark functions shows a marked improvement in performance over the original BFO.
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