Engineers have been continually striving to improve the efficiency of conventional problem-solving techniques for problems in several fields. In recent years, an increasing role of soft computing in civil engineering related areas has been observed, leading to many exciting and innovative applications. Soft computing methods are problem-solving strategies that are used to find approximate solutions to complex problems. Biologically inspired methods such as Artificial Neural Networks (ANN), Machine Learning (ML), Evolutionary Algorithms (EA), Swarm Intelligence and Fuzzy Logic are a few examples of soft computing methods. These methods are mainly inspired by the strategies that nature uses to solve problems. Most frequently, they are employed to substitute or enhance complex and computationally intensive mathematical models that have proved intractable for conventional analysis based on hard computing strategies.

This Special Issue will provide an overview of the present thinking and state-of-the-art developments on the application of soft computing and artificial intelligence techniques in civil engineering. The proposed collection of papers will include original research and review articles from scientists and engineers working in different areas of soft computing, covering all aspects related to civil engineering.

Potential topics include but are not limited to the following:

• Structural engineering
• Hydraulic engineering
• Transportation engineering
• Computational mechanics
• Structural health monitoring
• Engineering materials (concrete, steel, composite materials, etc)
• Geotechnical engineering
• Environmental engineering
• Design optimization
• Performance based design