On population variance and explorative power of invasive weed optimization algorithm
Prithwish Chakraborty, Gourab Ghosh Roy, Swagatam Das, Bighnaraj Panigrahi · 2009
Theoretical analysis of mataheuristic algorithms is believed to be very important for understanding their internal search mechanism and thus to develop more efficient algorithms. In this article we present a simple mathematical analysis of the explorative search behavior of a recently developed metaheuristic algorithm called Invasive Weed Optimization (IWO). IWO is a novel ecologically inspired algorithm that mimics the process of weeds colonization and distribution. This work analyses the evolution of the population-variance over successive generations in IWO and thereby draws some important conclusions regarding the explorative power of the same. Experimental results have been provided to validate the theoretical treatment.