Journal of Computational Physics
Penalty guided genetic search for reliability design optimization
Computers and Industrial Engineering
Mechanical engineering design optimization by differential evolution
New ideas in optimization
Evolution and Optimum Seeking: The Sixth Generation
Evolution and Optimum Seeking: The Sixth Generation
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Use of chaotic sequences in a biologically inspired algorithm for engineering design optimization
Expert Systems with Applications: An International Journal
Journal of Global Optimization
Expert Systems with Applications: An International Journal
Differential evolution and threshold accepting hybrid algorithm for unconstrained optimisation
International Journal of Bio-Inspired Computation
Two hybrid differential evolution algorithms for engineering design optimization
Applied Soft Computing
A modified harmony search threshold accepting hybrid optimization algorithm
MIWAI'11 Proceedings of the 5th international conference on Multi-Disciplinary Trends in Artificial Intelligence
A real-integer-discrete-coded differential evolution
Applied Soft Computing
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Realistic problems of structural optimization are characterized by non-linearity, non-convexity and by continuous and/or discrete design variables. There are non-linear dependencies between the optimised parameters. Real-world problems are rarely decomposable or separable. In this contribution a combined heuristic algorithm is described which is well suited for problems, for which the application-requirements of gradient-based algorithms are not fulfilled. The present contribution describes a combination of the Threshold Accepting Algorithm with Differential Evolution with particular emphasis on structural optimization, it can be classified as a Hybrid Evolutionary Algorithm. The Threshold Accepting Algorithm is similar to Simulated Annealing. Differential Evolution is based on Genetic Algorithms.