ACM Transactions on Mathematical Software (TOMS)
Multiple-Way Network Partitioning
IEEE Transactions on Computers
Vertex and edge partitions of graphs
Vertex and edge partitions of graphs
An improved spectral graph partitioning algorithm for mapping parallel computations
SIAM Journal on Scientific Computing
Recent directions in netlist partitioning: a survey
Integration, the VLSI Journal
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Partitioning of VLSI circuits and systems
DAC '96 Proceedings of the 33rd annual Design Automation Conference
Multilevel hypergraph partitioning: application in VLSI domain
DAC '97 Proceedings of the 34th annual Design Automation Conference
Multilevel circuit partitioning
DAC '97 Proceedings of the 34th annual Design Automation Conference
Greedy, Prohibition, and Reactive Heuristics for Graph Partitioning
IEEE Transactions on Computers
Genetic Algorithm and Graph Partitioning
IEEE Transactions on Computers
A Min-max Cut Algorithm for Graph Partitioning and Data Clustering
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Geometric mesh partitioning: implementation and experiments
IPPS '95 Proceedings of the 9th International Symposium on Parallel Processing
A linear-time heuristic for improving network partitions
DAC '82 Proceedings of the 19th Design Automation Conference
An Effective Multilevel Algorithm for Bisecting Graphs and Hypergraphs
IEEE Transactions on Computers
A Combined Evolutionary Search and Multilevel Optimisation Approach to Graph-Partitioning
Journal of Global Optimization
An effective multilevel tabu search approach for balanced graph partitioning
Computers and Operations Research
Genetic approaches for graph partitioning: a survey
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Graph partitioning algorithms for optimizing software deployment in mobile cloud computing
Future Generation Computer Systems
Hi-index | 14.98 |
A new heuristic algorithm, PROBE BA, based onthe recently introduced metaheuristic paradigm PROBE (PopulationReinforced Optimization Based Exploration) is proposedfor solving the Graph Partitioning Problem. The "exploration"part of PROBE BA is implemented using the Differential-Greedyalgorithm of Battiti and Bertossi and a modification of theKernighan and Lin algorithm at the heart of Bui and Moon'sGenetic Algorithm, BFS GBA. Experiments are used to investigateproperties of PROBE and show that PROBE BA comparesfavourably with other solution methods based on Genetic Algorithms,Randomized Reactive Tabu Search, or more specializedmultilevel partitioning techniques. In addition, PROBE BA findsnew best cut values for 10 of the 34 instances in Walshaw's GraphPartitioning Archive.