Combinatorial optimization: algorithms and complexity
Combinatorial optimization: algorithms and complexity
A study of permutation crossover operators on the traveling salesman problem
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Multiple-Way Network Partitioning
IEEE Transactions on Computers
New faster Kernighan-Lin-type graph-partitioning algorithms
ICCAD '93 Proceedings of the 1993 IEEE/ACM international conference on Computer-aided design
Multilevel k-way partitioning scheme for irregular graphs
Journal of Parallel and Distributed Computing
Multiway partitioning with pairwise movement
Proceedings of the 1998 IEEE/ACM international conference on Computer-aided design
Greedy, Prohibition, and Reactive Heuristics for Graph Partitioning
IEEE Transactions on Computers
Partitioning graphs on message-passing machines by pairwise mincut
Information Sciences—Informatics and Computer Science: An International Journal
Performance driven multi-level and multiway partitioning with retiming
Proceedings of the 37th Annual Design Automation Conference
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
AllelesLociand the Traveling Salesman Problem
Proceedings of the 1st International Conference on Genetic Algorithms
A Hybrid Genetic Search For Circuit Bipartitioning
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
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
Topological crossover for the permutation representation
GECCO '05 Proceedings of the 7th annual workshop on Genetic and evolutionary computation
Fitness Landscapes, Memetic Algorithms, and Greedy Operators for Graph Bipartitioning
Evolutionary Computation
Multi-attractor gene reordering for graph bisection
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Geometric crossover for multiway graph partitioning
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Normalization in genetic algorithms
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Geometric crossover for biological sequences
EuroGP'06 Proceedings of the 9th European conference on Genetic Programming
Feasibility-preserving crossover for maximum k-coverage problem
Proceedings of the 10th annual conference on Genetic and 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
Representation invariant genetic operators
Evolutionary Computation
Variable neighborhood multiobjective genetic algorithm for the optimization of routes on IP networks
EMO'11 Proceedings of the 6th international conference on Evolutionary multi-criterion optimization
Genetic approaches for graph partitioning: a survey
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Geometry of evolutionary algorithms
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
SBV-Cut: Vertex-cut based graph partitioning using structural balance vertices
Data & Knowledge Engineering
Quotient geometric crossovers and redundant encodings
Theoretical Computer Science
Geometry of evolutionary algorithms
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
EvoGeneSys, a new evolutionary approach to graph generation
Applied Soft Computing
Exploration and exploitation in evolutionary algorithms: A survey
ACM Computing Surveys (CSUR)
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Geometric crossover is a representation-independent generalization of the traditional crossover defined using the distance of the solution space. By choosing a distance firmly rooted in the syntax of the solution representation as a basis for geometric crossover, one can design new crossovers for any representation. Using a distance tailored to the problem at hand, the formal definition of geometric crossover allows us to design new problem-specific crossovers that embed problem-knowledge in the search. The standard encoding for multiway graph partitioning is highly redundant: each solution has a number of representations, one for each way of labeling the represented partition. Traditional crossover does not perform well on redundant encodings. We propose a new geometric crossover for graph partitioning based on a labeling-independent distance that filters out the redundancy of the encoding. A correlation analysis of the fitness landscape based on this distance shows that it is well suited to graph partitioning. A second difficulty with designing a crossover for multiway graph partitioning is that of feasibility: in general recombining feasible partitions does not lead to feasible offspring partitions. We design a new geometric crossover for permutations with repetitions that naturally suits partition problems and we test it on the graph partitioning problem. We then combine it with the labeling-independent crossover and obtain a much superior geometric crossover inheriting both advantages.