• Corpus ID: 17105754

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… 
1 Citations

Figures from this paper

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

References

SHOWING 1-10 OF 17 REFERENCES
A Survey of Parallel Genetic Algorithms
TLDR
This survey attempts to collect, organize, and present in a unified way some of the most representative publications on parallel genetic algorithms.
A Cultural Algorithm with Differential Evolution to Solve Constrained Optimization Problems
TLDR
A cultural algorithm is proposed that uses differential evolution as a population space and introduces an influence function that selects the source of knowledge to apply the evolutionary operators.
Using cultural algorithms to evolve strategies in agent-based models
TLDR
A methodology for the use of cultural algorithms to optimize strategies in agent-based models is presented and is demonstrated in an application used to model pricing strategies in the context of an agent- based model under a simulated real-world market scenario and a heterogeneous population.
AN INTRODUCTION TO CULTURAL ALGORITHMS
TLDR
It is shown how the addition of a belief space to the traditional Genetic Algorithm framework can affect the rate at which learning can take place in terms of the modifications that it produces in the traditional schema theorem for Genetic Algorithms.
Society and civilization: An optimization algorithm based on the simulation of social behavior
TLDR
The driving concept behind the optimization algorithm introduced in this paper that makes use of the intra and intersociety interactions within a formal society and the civilization model to solve single objective constrained optimization problems.
An Advanced Island Based GA For Optimization Problems
TLDR
A new paradigm for static/dynamic optimization based on an Island-Based Genetic Algorithm (IGA), aiming to apply the technology of Autonomous Agents in design and implementation of IGA.
Efficient and Accurate Parallel Genetic Algorithms
  • E. Cantú-Paz
  • Geology
    Genetic Algorithms and Evolutionary Computation
  • 2001
TLDR
The Gambler's Ruin and Population Sizing is illustrated by a comparison of Master-Slave Parallel GAs with Markov Chain Models of Multiple Demes.
A multipopulation cultural algorithm for the electrical generator scheduling problem
A novel multi-population cultural algorithm adopting knowledge migration
TLDR
Simulation results indicate that the proposed novel multi-population cultural algorithm adopting knowledge migration can effectively improve the speed of convergence and overcome premature convergence.
...
...