Using genetic algorithms to generate Steiner triple systems

Authors:
Stephen J. Hartley;Aaron H. Konstam
Affiliations:
Math and Computer Science Department, Drexel University, Philadelphia, PA;Department of Computer Science, Trinity University, San Antonio, TX
Venue:
CSC '93 Proceedings of the 1993 ACM conference on Computer science
Year:
1993

Citing 6
Cited 1

Applications of combinatorial designs in computer science

ACM Computing Surveys (CSUR)
Using genetic algorithms to solve NP-complete problems

Proceedings of the third international conference on Genetic algorithms
Adaptation in natural and artificial systems

Adaptation in natural and artificial systems
Solving the n-queens problem using genetic algorithms

SAC '92 Proceedings of the 1992 ACM/SIGAPP symposium on Applied computing: technological challenges of the 1990's
Optimization in a distributed processing environment using genetic algorithms with multivariate crossover

CSC '92 Proceedings of the 1992 ACM annual conference on Communications
Genetic Algorithms in Search, Optimization and Machine Learning

Genetic Algorithms in Search, Optimization and Machine Learning

Steiner systems and the Boolean satisfiability problem

SAC '96 Proceedings of the 1996 ACM symposium on Applied Computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

Steiner systems, particularly triple systems, are usually generated by mathematicians using techniques from the theory of groups and quasi-groups. When pencil-and-paper enumeration becomes infeasible, mathematicians have used computers to carry out exhaustive searches. This paper presents some results of using genetic algorithms, which do not use exhaustive search, to generate Steiner systems. A specialized mutation operator was effective in generating Steiner triple systems. Future research will focus on improving the genetic algorithm to generate higher order Steiner systems whose existence is not currently known.