A Novel Stochastic Optimization Algorithm Inspired From The Biology Of Plant Reproduction
Kinattingal Sundareswaran, Arnab Bhattacharjee · 2019
This paper proposes a novel stochastic optimization algorithm based on the biology of plant reproduction system. The plants are taken as solution variables and distributed in the solution space. The plant with highest fitness value is assumed to be in a fertile land with suitable climatic conditions and is made to disperse several seeds randomly in the solution space. The other lesser fit plants scatter fewer seeds around themselves, the number of seeds being made directly proportional to the plant's fitness. The process is repeated till convergence is attained. The new method is tested on standard test functions and the results obtained are promising. A comparison of the new method with Particle swarm Optimization (PSO) and Genetic Algorithm (GA) shows relatively improved convergence characteristics.