Theoretical analysis of garden balsam optimization algorithm

Abstract

Garden balsam optimization (GBO) is a new proposed evolutionary algorithm based on swarm intelligence. Convergence and time complexity analyses are very important in evolutionary computation, but the research on GBO is still blank. Same as other evolutionary algorithms, the optimization process of the GBO algorithm can be regarded as a Markov process. In this paper, a Markov stochastic model of the GBO algorithm is defined and used to prove the convergence of GBO algorithm. Finally, the approximation region of the estimated convergence time of GBO algorithm is calculated, which characterizes the evolution of the evolutionary process of the proposed algorithm.