Open AccessMulti-criteria optimization of reinforced concrete beams using genetic algorithms
Author(s) -
Ashot Tamrazyan,
Anatoly Alekseytsev
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/869/5/052027
Subject(s) - reinforced concrete , mathematical optimization , selection (genetic algorithm) , genetic algorithm , relation (database) , set (abstract data type) , process (computing) , computer science , iterative and incremental development , optimal design , algorithm , beam (structure) , base (topology) , optimization problem , structural engineering , mathematics , engineering , data mining , artificial intelligence , machine learning , mathematical analysis , software engineering , programming language , operating system
A strategy for finding optimal solutions for beam reinforced concrete structures according to several criteria has been proposed. The analysis and systematization of the optimization objectives for reinforced concrete framed systems is performed. To solve the problem, a modified genetic algorithm is used, which involves the selection of design options in a single iterative process into several databases containing solutions for each target criterion. When forming the current set of solutions, the migration of the best options from any base under consideration is allowed. As a general criterion of optimality, the J. Nash equilibrium principle is considered for penalties under failure to comply with constraints in relation to reinforced concrete structures.