Abstract

Social emotional optimization algorithm (SEOA) is a new swarm intelligent technique by simulating human social behaviors. In SEOA, each individual represents a virtual person and pursues high society status by selecting the behaviors according to the corresponding emotional index in each iteration. Therefore, how to simulate the personal decision mechanism plays an important role for the algorithm performance. In this paper, group decision mechanism is introduced into methodology of SEOA to simulate the human decision phenomenon. In this new variant, each person will make his decision not only with his experiences, but also with other individuals' experiences. To test the performance, four famous unconstraint numerical benchmarks are selected, and simulation results show it is effective when compared with other three swarm intelligent algorithms especially for high-dimensional cases.

Key words: Social emotional optimization algorithm, group decision mechanism, emotional index.

Abbreviation

SEOA, Social emotional optimization algorithm; SI, swarm intelligence; ACO, ant colony optimizer; SPSO, standard particle swarm optimization; MPSO-TVAC, modified particle swarm optimizxation with time-varying accelerator coefficients.