A New Approach to Global Optimization Motivated by Parliamentary Political Competitions

Several biology inspired optimization algorithms such as Genetic Algorithms, Ant Colony Optimization (ACO)and Particle Swarm Optimization (PSO) have previously been proposed by researchers. Recent approaches in numerical optimization have shifted to motivate from complex human social behaviors. In this paper, a new optimization algorithm, namely parliamentary optimization algorithm (POA) is proposed by studying the competitive and collaborative behaviors of political parties in a parliament. Experimental results reveal that our proposed approach is superior to PSO approach over some benchmark multidimensional functions.