Earthquake engineering

Epistemology

Swarm intelligence

Machine learning

Engineering

Intuition

Industrial engineering

Philosophy

Computational intelligence

Soft computing

Artificial intelligence

Heuristic

Computer science

Artificial neural network

Management science

Structural engineering

Particle swarm optimization

Engineering Structures

Although civil engineering problems are often characterized by significant levels of complexity, they are generally approached and solved by combining several practitioners’ skills, such as intuition, past experience, logical reasoning, mathematical elaborations, and physical sense. This is also the case of problems in structural and earthquake engineering whose solution is generally based on the so-called “engineer’s judgment”. However, heuristic theories and algorithms within the framework of “soft computing” can provide a more rational and systematic way to approach and solve problems in these areas. As a matter of fact, the aforementioned algorithms have been recently utilized in several branches of engineering and applied sciences. This paper proposes a state-of-the-art review of the main applications of soft computing techniques to relevant structural and earthquake engineering problems. Specifically, the applications of fuzzy computing, evolutionary computing, swarm intelligence, and neural networks, as well as their hybrid combinations, are analyzed with the aim to examine their capability and limitations in modeling, simulation, and optimization problems.

Soft computing techniques in structural and earthquake engineering: a literature review