# Revolutionary Algorithms

@article{Hochreiter2014RevolutionaryA, title={Revolutionary Algorithms}, author={Ronald Hochreiter and Christoph Waldhauser}, journal={ArXiv}, year={2014}, volume={abs/1401.4714} }

The optimization of dynamic problems is both widespread and difficult. When conducting dynamic optimization, a balance between reinitialization and computational expense has to be found. There are multiple approaches to this. In parallel genetic algorithms, multiple sub-populations concurrently try to optimize a potentially dynamic problem. But as the number of sub-population increases, their efficiency decreases. Cultural algorithms provide a framework that has the potential to make…

## One Citation

Solving dynamic optimisation problems with revolutionary algorithms

- Business, Computer Science
- 2013

The superiority of revolutionary algorithms over cultural and purely genetic algorithms is demonstrated in the solving of a standard dynamic facility location problem.

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