An automated optimal design method using hybrid genetic algorithm (GA) is developed for pile group foundation design. The design process is a sizing and topology optimization for pile group foundations. Given the site geology, loadings and design considerations, a pile group with close-to-minimum volume of material is sought by the optimization program. Design variables are the configuration, number and cross sectional dimensions of the piles as well as the thickness of the pile cap....[ Read more ]

An automated optimal design method using hybrid genetic algorithm (GA) is developed for pile group foundation design. The design process is a sizing and topology optimization for pile group foundations. Given the site geology, loadings and design considerations, a pile group with close-to-minimum volume of material is sought by the optimization program. Design variables are the configuration, number and cross sectional dimensions of the piles as well as the thickness of the pile cap.

In order to tackle the major shortcoming of GA, namely large computation effort in searching the optimum design and poor local search capability, a local search operator by the fully stressed design approach (FSD operator) is incorporated into classical simple genetic algorithm.

The effectiveness and capability of the proposed algorithm is verified with illustrative examples of 5 by 5 pile groups under different loading conditions. The optimization results match the engineering expectation and the FSD operator has great improvement on both design quality and convergence rate. The hybridization of genetic algorithm and the local search operator is examined and the rate of the FSD operator is suggested for pile group designs.

The proposed optimization algorithm is extended to a large scale foundation project to demonstrate the practicality of the algorithm. Challenges encountered in the application of optimization techniques on design of pile groups consisting of hundreds of piles are discussed. The proposed hybrid genetic algorithm successfully minimizes the volume of material consumption and the result matches the engineering expectation.