A fast algorithm for generating set partitions
The Computer Journal
Niching methods for genetic algorithms
Niching methods for genetic algorithms
Analysis of Algorithms for Listing Equivalence Classes of k-ary Strings
SIAM Journal on Discrete Mathematics
ACM Computing Surveys (CSUR)
How to solve it: modern heuristics
How to solve it: modern heuristics
Genetic Algorithms and Grouping Problems
Genetic Algorithms and Grouping Problems
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
AllelesLociand the Traveling Salesman Problem
Proceedings of the 1st International Conference on Genetic Algorithms
Genetic algorithms, path relinking, and the flowshop sequencing problem
Evolutionary Computation
Learning the structure of dynamic probabilistic networks
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Variable grouping in multivariate time series via correlation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Efficiency updates for the restricted growth function GA for grouping problems
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Data Partitioning in Data Warehouses: Hardness Study, Heuristics and ORACLE Validation
DaWaK '08 Proceedings of the 10th international conference on Data Warehousing and Knowledge Discovery
Computers and Operations Research
ICANNGA'09 Proceedings of the 9th international conference on Adaptive and natural computing algorithms
A genetic clustering algorithm using a message-based similarity measure
Expert Systems with Applications: An International Journal
Formal analysis, hardness, and algorithms for extracting internal structure of test-based problems
Evolutionary Computation
A wide-ranging computational comparison of high-performance graph colouring algorithms
Computers and Operations Research
Exploiting domain knowledge in system-level MPSoC design space exploration
Journal of Systems Architecture: the EUROMICRO Journal
Hi-index | 0.01 |
There is substantial research into genetic algorithms that are used to group large numbers of objects into mutually exclusive subsets based upon some fitness function. However, nearly all methods involve degeneracy to some degree.We introduce a new representation for grouping genetic algorithms, the restricted growth function genetic algorithm, that effectively removes all degeneracy, resulting in a more efficient search. A new crossover operator is also described that exploits a measure of similarity between chromosomes in a population. Using several synthetic datasets, we compare the performance of our representation and crossover with another well known state-of-the-art GA method, a strawman optimisation method and a well-established statistical clustering algorithm, with encouraging results.