Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
An updated survey of GA-based multiobjective optimization techniques
ACM Computing Surveys (CSUR)
Evolutionary Algorithms in Engineering Applications
Evolutionary Algorithms in Engineering Applications
The Design of Innovation: Lessons from and for Competent Genetic Algorithms
The Design of Innovation: Lessons from and for Competent Genetic Algorithms
Evolutionary Computing: The Rise of Electronic Breeding
IEEE Intelligent Systems
Damage assessment of structures using hybrid neuro-genetic algorithm
Applied Soft Computing
Crack detection in beam-like structures using genetic algorithms
Applied Soft Computing
Fuzzy reliability analysis of deep sliding plane in rock foundation under dam
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 6
Digital IIR filter design using multi-objective optimization evolutionary algorithm
Applied Soft Computing
A modified gravitational search algorithm for slope stability analysis
Engineering Applications of Artificial Intelligence
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The slope stability analysis is routinely performed by engineers to evaluate the stability of embankment dams, road embankments, river training works, excavations and retaining walls. Locating the critical failure surface of a soil slope is rendered erroneous and cumbersome due to the existence of local minima points. In case of large soil slopes, engineers face with a search space too large to employ the trial and error method in a computationally efficient fashion. A genetic algorithm is proposed to locate the critical surface under general conditions with general constraints. Convergence to any prescribed degree of precision was achieved with the algorithm. The algorithm has been demonstrated to be computationally superior to other optimization routines, like, Monte-Carlo method and grid-points approach.