• 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.
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 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
Evolved election forecasts: using genetic algorithms in improving election forecast results
TLDR
It is shown that the proposed method outperforms currently applied approaches and thereby provides an argument to tighten the intersection between computer science and social science, especially political science, further.
Dynamic Optimization for Reachability Problems
This paper uses dynamic programming techniques to describe reach sets andrelated problems of forward and backward reachability. The original problemsdo not involve optimization criteria and are
A Stochastic Calculus Model of Continuous Trading: Optimal Portfolios
  • S. Pliska
  • Economics, Mathematics
    Math. Oper. Res.
  • 1986
TLDR
The problem of choosing a portfolio of securities so as to maximize the expected utility of wealth at a terminal planning horizon is solved via stochastic calculus and convex analysis and a martingale representation problem is developed.
Practical Genetic Algorithms
Introduction to Optimization The Binary Genetic Algorithm The Continuous Parameter Genetic Algorithm Applications An Added Level of Sophistication Advanced Applications Evolutionary Trends Appendix
...
...