Submission Deadline: 30 November 2025 View: 1093 Submit to Special Issue
Prof. Dr. Gebrail Bekdaş, Istanbul University–Cerrahpaşa, Turkey
Prof. Dr. Sinan Melih Nigdeli, Istanbul University–Cerrahpaşa, Turkey
Prof. Dr. Zong Woo Geem, Gachon University, South Korea
Soft computing and advanced optimization techniques have become indispensable tools in modern civil engineering. The complexities involved in civil engineering projects, such as designing large-scale structures or optimizing transportation networks, often require tackling intricate multi-constraint and multi-objective problems. Traditional optimization methods can struggle with these challenges due to the nonlinearity and high dimensionality of the problems involved.
This is where metaheuristic algorithms shine. They emulate natural processes like evolution, swarm behavior, or physical processes to efficiently explore complex solution spaces and find near-optimal solutions. Algorithms such as genetic algorithms, particle swarm optimization, simulated annealing, and ant colony optimization are widely used in civil engineering for tasks ranging from structural optimization to traffic management.
The key advantages of these algorithms lie in their ability to handle non-convex and discontinuous objective functions, as well as to efficiently navigate large solution spaces where traditional gradient-based methods might fail or become computationally prohibitive. Additionally, metaheuristics can incorporate multiple objectives and constraints, providing engineers with a suite of tools to balance trade-offs between safety, cost, environmental impact, and other critical factors.
By leveraging the strengths of various metaheuristic algorithms or combining them with domain-specific knowledge, engineers can achieve superior design outcomes. For example, hybrid approaches that integrate metaheuristics with machine learning can offer prediction of optimum results.
Overall, the integration of soft computing and AI techniques into civil engineering practices has revolutionized the field by enabling engineers to tackle complex design challenges more effectively and efficiently, ultimately leading to safer, more sustainable, and aesthetically pleasing infrastructure.
The novel interest in applying soft computing and AI techniques to civil engineering lies not only in the technical advancements but also in the transformative ways these technologies are reshaping the field, fostering interdisciplinary collaboration, and addressing critical sustainability challenges facing modern infrastructure development. This factor shows good relevance to the scope of the journal of the proposed theme.
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