Abstract
Three decades ago, new families of computational methods, denoted as soft computing methods, were proposed. These methods are based on heuristic approaches rather than on rigorous mathematics. Despite the fact that these methods were initially received with suspicion, they have turned out in many cases to be surprisingly powerful, while their use in various areas of engineering science is continuously growing. Soft computing search algorithms such as evolutionary programming, genetic algorithms, and evolution strategies, among others, have been inspired by natural phenomena. Recently, new search algorithms have been proposed that are based on the simulation of social interactions between members of a specific species or algorithms inspired by the improvisation process of musicians. In this chapter, two optimization problems are considered for assessing the performance of metaheuristics. In particular, the problem of infrastructure network restoration and minimization of the adverse impacts of natural hazards on civil infrastructure and the problem of reliability analysis of geostructures, which is formulated as an optimization problem, are considered.
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