Plant growth simulation algorithm based on double growth point parallel growth mechanism and its structural optimization

Plant growth simulation algorithm (PGSA) and its improved algorithms still have the defects of relatively single search path, insufficient search coverage and so on. The complex structural optimization problems have the characteristics of multiple design variables, multiple local optimal solutions, difficulty in automatic terminate and so on. In order to address the above defects and characteristics, a new algorithm mechanism (double growth point parallel growth mechanism) is proposed based on the basic principle of PGSA and the actual growth law of plants. This new mechanism is also integrated with GSL&PS-PGSA (growth space limitation & parallel search) algorithm. The effectiveness of the proposed mechanism is verified by typical mathematic examples and structural example of space truss. The results show that the double growth point parallel growth mechanism can increase search paths, widen search area, and reduce the probability of falling into local optimal solution. It provides a more effective termination mechanism for the algorithm, and thus encourages more significant optimization efficiency and global search ability of the algorithm. Compared with other commonly used optimization methods such as Sequential two-level algorithm and Ant colony algorithm, the GSL&PS-PGSA with the double growth point parallel growth mechanism further improves the optimization ability. It shows fine adaptability and effectiveness in structural optimization problems.