Abstract

SummaryThis paper introduces a method called garden balsam optimization algorithm (GBO) for optimization problems. Garden balsam randomly ejects the seeds within a certain range by virtue of mechanical force originating from cracking of mature seed pods. The seeds scattered to suitable growth area will have greater reproductive capacity in the next generation, followed by iteration until the most suitable point for growth in a particular space is eventually found. Mimicking the transmission of garden balsam seeds, GBO generates the seeds by the mechanical transmission and second transmission operator to search the global optimum in the problem space. The convergence of GBO is tested in details through a set of benchmark multi‐dimensional functions. Secondly, the effect of tuning parameters on algorithm performance is studied. Finally, several typical problems were selected in the standard test set to test the performance of GBO. The experimental results show that the algorithm has advantages in optimization problems. In conclusion, the performance of GBO has a reasonable performance for all the test functions.

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