A Comparative Analysis of Swarm Intelligent Algorithms

A Black box program is one where the user cannot see the inner workings or one which has no side effects and the function of which need not be examined. Nature-inspired computing (NIC) or bio-inspired computing focuses on designing and developing computer algorithms and models using principles adopted from biology. Swarm intelligent algorithms (SIA) are bio-inspired algorithms developed based on the interactions between living organisms such as flocks of birds, ants, and fish. Swarm intelligence (SI) is one of the computational intelligence techniques used to solve complex problems. It is a reliable technique that has been used for treating several optimization problems. The two Swarm intelligent algorithms used for this research are particle swarm optimization (PSO) and Artificial Bee Colony (ABC) algorithm. The corresponding modified guided algorithms PSO-Guided and ABC-Guided are proposed. The proposed guided approach utilizes the current global best solution to guide the algorithm out of the local minima. The study finds that the guided methods outperform the standard algorithms in finding the best solution.