RELATIVE STUDY OF CGS WITH ACO AND BCO SWARM INTELLIGENCE TECHNIQUES

Abstract

Swarm intelligence is the collective-level, problem-solving behavior of groups of relatively simple agents. Local interactions among agents, either direct or indirect through the environment, are fundamental for the emergence of swarm intelligence. Ant Colony Optimization (ACO) is a swarm based meta-heuristic method that is inspired by the behavior of real ant colonies. Bee Colony Optimization (BCO) meta-heuristic belongs to the groupof Swarm Intelligence techniques. Consultant Guided Search (CGS) is a new hybrid meta heuristic, which combinesnew ideas with concepts found in Ant colony Optimization (ACO), Bee Colony Optimization (BCO) technique. Thispaper presents comparative study of CGS, ACO, BCO techniques and the flexibility of CGS.