Proceedings of the third international conference on Genetic algorithms
`` Direct Search'' Solution of Numerical and Statistical Problems
Journal of the ACM (JACM)
An Introduction to Genetic Algorithms for Scientists and Engineers
An Introduction to Genetic Algorithms for Scientists and Engineers
Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Uniform Crossover in Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Advances in Engineering Software
Structural and Multidisciplinary Optimization
Design of prestressed concrete flat slab using modern heuristic optimization techniques
Expert Systems with Applications: An International Journal
A survey of non-gradient optimization methods in structural engineering
Advances in Engineering Software
Hi-index | 0.00 |
This paper presents a two-stage hybrid optimization algorithm based on a modified genetic algorithm. In the first stage, a global search is carried out over the design search space using a modified GA. The proposed modifications on the basic GA includes dynamically changing the population size throughout the GA process and the use of different forms of the penalty function in constraint handling. In the second stage, a local search based on the genetic algorithm solution is executed using a discretized form of Hooke and Jeeves method. The hybrid algorithm and the modifications to the basic genetic algorithm are examined on the design optimization of reinforced concrete flat slab buildings. The objective function is the total cost of the structure including the cost of concrete, formwork, reinforcement and foundation excavation. The constraints are defined according to the British Standard BS8110 for reinforced concrete structures. Comparative studies are presented to study the effect of different parameters of handling genetic algorithm on the optimized flat slab building. It has been shown that the proposed hybrid algorithm can improve genetic algorithm solutions at the expense of more function evaluations.