Journal of Computational Physics
Improved genetic operators for structural engineering optimization
Advances in Engineering Software
Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
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
Tabu Search
Cost Optimization of Structures: Fuzzy Logic, Genetic Algorithms, and Parallel Computing
Cost Optimization of Structures: Fuzzy Logic, Genetic Algorithms, and Parallel Computing
Design of reinforced concrete bridge frames by heuristic optimization
Advances in Engineering Software
An efficient simulated annealing algorithm for design optimization of truss structures
Computers and Structures
Evolutionary computation and structural design: A survey of the state-of-the-art
Computers and Structures
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Design of reinforced concrete road vaults by heuristic optimization
Advances in Engineering Software
Expert Systems with Applications: An International Journal
Analysis of arbitrary composite sections in biaxial bending and axial load
Computers and Structures
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This paper deals with the economic optimization of reinforced concrete (RC) bridge piers with hollow rectangular sections and describes the efficiency of three heuristic algorithms: two new variants of the ant colony optimization (ACO) algorithm, the genetic algorithm (GA) and the threshold acceptance (TA) algorithm. The GA and TA are used for comparison with the new ACO algorithms. The total number of variables is 95. All variables are discrete in this analysis. The calibration of the new ACO algorithm recommended a 250-member ant population and 100 stages. The best solution costs 69,467 euros, which means savings of about 33% as compared to experience-based design. Finally, results indicate that the new ACO algorithms are potentially useful for optimizing the costs of real RC structures.