Plant Biology-Inspired Genetic Algorithm: Superior Efficiency to Firefly Optimizer

This chapter analytically compares the efficiency of the recent plant biology-inspired genetic algorithm (PBGA) and the firefly algorithm (FA) optimizer. The comparison is over a range of well-known critical benchmark test functions. Through statistical comparisons over the benchmark functions, the efficiency of PBGA has been evaluated versus FA as a well-known accurate meta-heuristic optimizer. Through a considerable number of Monte Carlo runs of searching for a solution by both optimizers, their performance has been statistically measured by several valid indices. In addition, the convergence curves give a visual comparison of both techniques where the stability, speed, and accuracy dominance of PBGA is clearly observable. However, in the case of benchmark function with smooth nature-like Rosenbrock, Sphere, and Dixon and Price, FA has better performance on average, while PBGA performance is still comparable to FA.

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