Using NW small-world model to improve the performance of social emotional optimization algorithm

Topology structure is an important aspect to influence the performance of social emotional optimization algorithm (SEOA).A good topology structure may provide more chance to escape from a local optimum, therefore, in this paper, a new topology structure-Newman and Watts small world model is introduced and called NWSEOA. In NWSEOA, the topology is changed according to Newman-Watts rules within the whole evolutionary process. To test the performance of NWSEOA, three other algorithms are employed including standard version and one variant of particle swarm optimization, and the standard version of SEOA, and 5 famous benchmarks are used to compare, simulation results show the proposed algorithm is superior to other three algorithms.