On population variance and explorative power of invasive weed optimization algorithm

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.