Future paths for integer programming and links to artificial intelligence
Computers and Operations Research - Special issue: Applications of integer programming
Simulated annealing and Boltzmann machines: a stochastic approach to combinatorial optimization and neural computing
LEDA: a platform for combinatorial and geometric computing
LEDA: a platform for combinatorial and geometric computing
New methods to color the vertices of a graph
Communications of the ACM
ESOA'06 Proceedings of the 4th international conference on Engineering self-organising systems
Heuristic colour assignment strategies for merge models in graph colouring
EvoCOP'05 Proceedings of the 5th European conference on Evolutionary Computation in Combinatorial Optimization
Note: Quantum annealing of the graph coloring problem
Discrete Optimization
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This paper presents a new heuristic algorithm for the graph coloring problem based on a combination of genetic algorithms and simulated annealing. Our algorithm exploits a novel crossover operator for graph coloring. Moreover, we investigate various ways in which simulated annealing can be used to enhance the performance of an evolutionary algorithm. Experiments performed on various collections of instances have justified the potential of this approach. We also discuss some possible enhancements and directions for further research.