GSO: A New Solution for Solving Unconstrained Optimization Tasks Using Garter Snake's Behavior
Maryam Naghdiani, Mohsen Jahanshahi · 2017
Solving the unconstrained optimization problems with swarm intelligent algorithms has received significant consideration recently. In this paper, a novel algorithm called GSO (Garter Snake Optimization) is proposed for solving unconstrained optimization tasks. In the proposed algorithm, individuals emulate a group of garter snakes, which interact to each other based on the biological laws of the cooperative colony. The explored solutions achieved by GSO are analyzed with that of well-known methods namely KA and PSO. The results show that GSO is competitive in comparison with the representative algorithms.