Abstract: As a new heuristic intelligent optimization algorithm，plant growth simulation algorithm (PGSA) esta- blishes the dynamic growth model based on the plant phototropism mechanism and forms the search mechanism rapid- ly towards the global optimal solution． According to the characteristics of large-scale complex optimization problems such as large growth space，multiple design variables，multiple local optimal solutions，difficulty in automatic ter- mination and so on，three novel improved mechanisms (the limited strategy of growth point set，the elimination strategy of new growth points，the parallel search strategy of mixed step size) were proposed based on the basic principle of PGSA and the effectiveness of the proposed improved mechanisms were proved by typical mathematic example and structural example of truss． Several conclusions can be drawn: (1) the scale of growth space can be effectively controlled by the limited strategy of growth point set，which leads to high search capacity of the algo- rithm; (2) combined with the former strategy，the elimination strategy of new growth points can provide effective termination mechanism for PGSA; (3) excellent global search capacity can be offered by the parallel search strate- gy of mixed step size in the early growth stage and the optimal solution range can be quickly obtained． The pro- posed mechanisms can dramatically improve the effectiveness and adaptability of PGSA in optimization，which pro- vides a new approach for structural optimization problems．

Key words: plant growth simulation algorithm, plant phototropism mechanism, structural optimization, parallel search, global optimal solution, truss structure