Future paths for integer programming and links to artificial intelligence
Computers and Operations Research - Special issue: Applications of integer programming
A contraction algorithm for finding small cycle cutsets
Journal of Algorithms
Efficient implementation of graph algorithms using contraction
Journal of the ACM (JACM)
Improving the performance of the Kernighan-Lin and simulated annealing graph bisection algorithms
DAC '89 Proceedings of the 26th ACM/IEEE Design Automation Conference
Introduction to algorithms
Facet identification for the symmetric traveling salesman polytope
Mathematical Programming: Series A and B
Combinatorial algorithms for integrated circuit layout
Combinatorial algorithms for integrated circuit layout
Solution of large-scale symmetric travelling salesman problems
Mathematical Programming: Series A and B
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Modern heuristic techniques for combinatorial problems
Vertex and edge partitions of graphs
Vertex and edge partitions of graphs
Ejection chains, reference structures and alternating path methods for traveling salesman problems
Discrete Applied Mathematics - Special volume: first international colloquium on graphs and optimization (GOI), 1992
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Introduction to Algorithms: A Creative Approach
Introduction to Algorithms: A Creative Approach
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
A Fast and Robust Network Bisection Algorithm
IEEE Transactions on Computers
The Differencing Method of Set Partitioning
The Differencing Method of Set Partitioning
Graph Theory With Applications
Graph Theory With Applications
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A heuristic optimization methodology, Dynamic Contraction (DC), is introduced as an approach for solving a widevariety of hard combinatorial problems. Contraction is an operation thatmaps an instance of a problem to a smaller instance of the same problem.DC is an iterative improvement strategy that relies on contraction as amechanism for escaping local minima. As a byproduct of contraction,efficiency is improved due to a reduction of problem size. Effectivenessof DC is shown through simple applications to two classicalcombinatorial problems: The graph bisection problem and the travelingsalesman problem.