This　paper　aims　to　improve　control　performance　for　a　magnetorheological　damper　(MRD)-based　semi-active　seat　suspension　system.　The　vibration　of　the　suspension　is　isolated　by　controlling　the　stiffness　of　the　MRD　using　a　proportion　integration　differentiation　(PID)　controller.　A　new　intelligent　method　for　optimizing　the　PID　parameters　is　proposed　in　this　work.　This　new　method　appropriately　incorporates　particle　swarm　optimization　(PSO)　into　the　PID-parameter　searching　processing　of　an　improved　fruit　fly　optimization　algorithm　(IFOA).　Thus,　the　PSO-IFOA　method　possesses　better　optimization　ability　than　IFOA　and　is　able　to　find　a　globally　optimal　PID-parameter　set.　The　performance　of　the　PID　controller　optimized　by　the　proposed　PSO-IFOA　for　attenuating　the　vibration　of　the　MRD　suspension　was　evaluated　using　a　numerical　model　and　an　experimental　platform.　The　results　of　both　simulation　and　experimental　analysis　demonstrate　that　the　proposed　PSO-IFOA　is　able　to　optimize　the　PID　parameters　for　controlling　the　MRD　semi-active　seat　suspension.　The　control　performance　of　the　PSO-IFOA-based　PID　is　superior　to　that　of　individual　PSO-,　FOA-,　or　IFOA-based　methods.