To　alleviate　premature　convergence　and　bloat　in　general　linear　genetic　programming,　a　modified　linear　genetic　programming　method　based　on　an　age-layered　population　model　is　proposed.　To　alleviate　premature　optimization　of　the　population,　we　first　applied　an　age-layered　population　model　to　linear　genetic　programming　to　improve　the　integral　population　diversity.　We　then　used　a　two-layer　tournament　to　improve　the　sub-population　diversity　in　each　layer,　improving　the　local　population　diversity　and　decreasing　the　occurrence　rate　of　premature　optimization　by　increasing　the　diversity　of　the　population.　To　control　the　bloat　effect　of　the　population,　the　age-layered　population　model　segregated　individuals　into　different　layers　based　on　age,　so　the　quantity　of　long-length　individuals　was　limited.　The　experimental　results　on　five　symbolic　regression　benchmark　functions　show　that　the　proposed　method　can　improve　population　diversity　to　reduce　premature　convergence　and　effectively　control　bloat.　©　2017,　Editorial　Department　of　Journal　of　HEU.　All　right　reserved.