NP-hard problems in hierarchical-tree clustering
Acta Informatica
Heuristic Algorithms for Task Assignment in Distributed Systems
IEEE Transactions on Computers
Simulated annealing: theory and applications
Simulated annealing: theory and applications
The allocation problem in parallel production systems
Journal of Parallel and Distributed Computing
VLSI cell placement techniques
ACM Computing Surveys (CSUR)
The knowledge base partitioning problem: mathematical formulation and heuristic clustering
Data & Knowledge Engineering
An efficient heuristic algorithm for mapping parallel programs onto multicomputers
Microprocessing and Microprogramming
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
IEEE Transactions on Computers
The noising method: a new method for combinatorial optimization
Operations Research Letters
Noising methods for a clique partitioning problem
Discrete Applied Mathematics - Special issue: IV ALIO/EURO workshop on applied combinatorial optimization
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Many heuristics such as iterative improvement and simulated annealing are available in the literature which try to give a near-optimal solution to the graph partitioning problem. Recently, a new method called the noising method has been proposed for solving combinatorial optimization problems. The noising method has been successfully employed to solve the clique partitioning problem. We extend the method to solve the graph partitioning problem. We also propose a modified noising method (algorithm) for efficient solution of the graph partitioning problem. We evaluate the performance of our algorithm for solving both the problems, viz., the clique partitioning problem using random graphs and the graph partitioning problem using concurrent VLSI circuit simulation program graphs. We compare our algorithm with the original noising and the simulated annealing algorithms. The results show that our modified noising algorithm compares favourably with the original noising and the simulated annealing algorithms, both in terms of the run time and the quality of the solutions obtained.