Optimum Design of Pile Foundation by Automatic Grouping Genetic Algorithms | Zendy

Xiaofeng Liu | Zendy; Gengdong Cheng | Zendy; Bo Wang | Zendy; Shu-Zhi Lin | Zendy

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Optimum Design of Pile Foundation by Automatic Grouping Genetic Algorithms

Author(s) -

Xiaofeng Liu,

Gengdong Cheng,

Bo Wang,

Shu-Zhi Lin

Publication year - 2012

Publication title -

isrn civil engineering

Language(s) - English

Resource type - Journals

eISSN - 2090-5114

pISSN - 2090-5106

DOI - 10.5402/2012/678329

Subject(s) - pile , genetic algorithm , modular design , optimal design , cardinality (data modeling) , constraint (computer aided design) , algorithm , foundation (evidence) , variable (mathematics) , mathematical optimization , code (set theory) , computer science , engineering , mathematics , data mining , programming language , set (abstract data type) , machine learning , mechanical engineering , history , mathematical analysis , archaeology

This paper studies the optimum conceptual design of pile foundations at the initial design stage. A modular method is proposed, which divides the foundation into modules and each module is identified by its characteristics of pile length, diameter, number and layout. Modules with the same characteristics may be packed and represented by a design variable. A minimum-cost optimization model with multiple design constraints based on Chinese code and a cardinality constraint is built to achieve the concurrent optimization of pile size and layout. The model is solved by the improved automatic grouping genetic algorithms to obtain the design with optimal variables and optimal variable grouping. A practical example demonstrates the effectiveness of the proposed approach.

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