Parallel version of self-configuring genetic algorithm application in spacecraft control system design

Authors:
Maria Semenkina
Affiliations:
Siberian State Aerospace University, Krasnoyarsk, Russian Fed.
Venue:
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Year:
2013

Citing 3
Cited 0

A dynamic Island-based genetic algorithms framework

SEAL'10 Proceedings of the 8th international conference on Simulated evolution and learning
Parameter control in evolutionary algorithms

IEEE Transactions on Evolutionary Computation
Self-configuring genetic algorithm with modified uniform crossover operator

ICSI'12 Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part I

Quantified Score

Hi-index	0.00

Visualization

Abstract

Technological and command-programming control contours of a spacecraft are modelled with Markov chains. These models are used for the preliminary design of spacecraft control system effective structure with the use of special DSS. Corresponding optimization problems with algorithmically given functions of mixed variables are solved with a special stochastic algorithm called self-configuring genetic algorithm that requires no settings determination and parameter tuning. The high performance of the suggested algorithm is proved by solving real problems of the control contours structure preliminary design.