Task Scheduling for a Multi-Robot System using Genetic Algorithm

@inproceedings{Hyon2015TaskSF,
  title={Task Scheduling for a Multi-Robot System using Genetic Algorithm},
  author={Ja-Young Hyon and Jinhan Jeong},
  year={2015}
}
In this paper, we present and solve a scheduling problem for a high-density robotic workcell under various working conditions. The genetic algorithm (GA) is employed to optimize tasks for scheduling of the multi-robot system. A new operation method for generating subsequent generations of GA, controlled mutation is introduced depending on the value of the objective function in order to help the algorithm get out of the local minimum. Several simulation graphs verify efficiency of the proposed… 

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References

SHOWING 1-8 OF 8 REFERENCES
Genetic K-means algorithm
TLDR
A novel hybrid genetic algorithm that finds a globally optimal partition of a given data into a specified number of clusters using a classical gradient descent algorithm used in clustering, viz.
Genetic Algorithms + Data Structures = Evolution Programs
If you are looking for Genetic Algorithms Data Structures Evolution Programs in pdf file you can find it here. This is the best place for you where you can find the genetic algorithms data structures
Optimal task scheduling for a two-robot workcell
  • Jaurnal of systems and control engineering, vol. 224. No. 7 845-855 November 2010
  • 2010
Aspragathos, “Optimal robot task scheduling based on genetic algorithms,”Robotics and Computer-Integrated Manufacturing
  • 2005
Optimal task scheduling for a two-robot workcell Jaurnal of systems and control engineering
  • Optimal task scheduling for a two-robot workcell Jaurnal of systems and control engineering
  • 2010