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Abstract
This paper represents the Glowworm Swarm Optimization Algorithm which solves the problem of garbage collection by using its mechanism which is originated by the social behavior and the phenomenon of bioluminescent communication of glowworms. The paper presents a solution to the problem of garbage collection by groups of autonomous robots. The algorithm is applied on the robots to manage their movement around the area containing garbage. Using this algorithm number of robots are trained to interact with each other, also finding the multiple optima of multimodal functions attempting to simulate the way a group of animals behave like a single cognitive entity. The simulation is carried in such a manner that the items are collected and then deposited in the desired stations. Finally, experiments are conducted using the benchmark functions to get the best fitness values for the robots. In the end the comparison is carried for GSO with PSO that is designed for the parallel computation of multiple optima.