Time optimal control of overhead cranes with hoisting of the load
Automatica (Journal of IFAC)
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Journal of Global Optimization
Structural and Multidisciplinary Optimization
An efficient dynamic load balancing algorithm
Computational Mechanics
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In this study a critical assessment of three metaheuristic optimization algorithms, namely differential evolution, harmony search and particle swarm optimization, is performed with reference to their efficiency and robustness for the optimum design of real-world structures. Furthermore, a neural network based prediction scheme of the structural response, required to assess the quality of each candidate design during the optimization procedure, is proposed. The proposed methodology is applied to an overhead crane structure using different finite element simulations corresponding to a solid discretization as well as mixed discretizations with shell-solid and beam-solid elements. The number of degrees of freedom (dof) resulted for the simulation of the structural response varies in the range of 60,000 to 1,400,000 dof leading to highly computational intensive problems.