Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Computing edge-connectivity in multigraphs and capacitated graphs
SIAM Journal on Discrete Mathematics
Finding good approximate vertex and edge partitions is NP-hard
Information Processing Letters
A general framework for vertex orderings, with applications to netlist clustering
ICCAD '94 Proceedings of the 1994 IEEE/ACM international conference on Computer-aided design
Greedy, Prohibition, and Reactive Heuristics for Graph Partitioning
IEEE Transactions on Computers
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Genetic Algorithm and Graph Partitioning
IEEE Transactions on Computers
A linear-time heuristic for improving network partitions
DAC '82 Proceedings of the 19th Design Automation Conference
Lock-Gain Based Graph Partitioning
Journal of Heuristics
New topologies for genetic search space
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Fitness Landscapes, Memetic Algorithms, and Greedy Operators for Graph Bipartitioning
Evolutionary Computation
On implementation choices for iterative improvement partitioning algorithms
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Geometric crossovers for multiway graph partitioning
Evolutionary Computation
An Enzyme-Inspired Approach to Surmount Barriers in Graph Bisection
ICCSA '08 Proceeding sof the international conference on Computational Science and Its Applications, Part I
Lower and upper bounds for linkage discovery
IEEE Transactions on Evolutionary Computation
Multiobjective evolutionary algorithms for dynamic social network clustering
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Genetic approaches for graph partitioning: a survey
Proceedings of the 13th annual conference on Genetic and evolutionary computation
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We propose a new gene reordering scheme for the graph bisection problem. Our gene reordering starts with two or more vertices to capture the clustering structure of graphs effectively. We devised a chromosome repairing method for hybrid genetic search, which helps exploit clusters when combined with gene reordering. Experimental tests showed that the suggested reordering scheme significantly improves the performance of genetic algorithms over previous reordering methods.