Research on Invasive Weed Optimization based on the cultural framework

Invasive weed optimization (IWO), which is inspired from the invasive habits of growth of weeds in nature, is a population-based intelligence algorithm. In this paper, the IWO is embedded into cultural framework as a population space of a cultural algorithm (CA), called cultural IWO. CA is mechanisms that incorporate generic knowledge sources obtained during the evolutionary process, which increases the efficiency of searching processes. Here, this situational knowledge and normative knowledge specifically designed according to the IWO evolution population are used to guide the evolution of the population, and they exploit the information sufficiently that the optimum individual carries and speed up the evolutionary process. The performance of the proposed method is evaluated by a number of test functions. Computational results reveal that the algorithm can be efficiently applied to the function optimization.