Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
The ant colony optimization meta-heuristic
New ideas in optimization
Weight-biased edge-crossover in evolutionary algorithms for two graph problems
Proceedings of the 2001 ACM symposium on Applied computing
A Population Based Approach for ACO
Proceedings of the Applications of Evolutionary Computing on EvoWorkshops 2002: EvoCOP, EvoIASP, EvoSTIM/EvoPLAN
AllelesLociand the Traveling Salesman Problem
Proceedings of the 1st International Conference on Genetic Algorithms
Scheduling Problems and Traveling Salesmen: The Genetic Edge Recombination Operator
Proceedings of the 3rd International Conference on Genetic Algorithms
Inver-over Operator for the TSP
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
A Modified Edge Recombination Operator for the Travelling Salesman Problem
PPSN III Proceedings of the International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature: Parallel Problem Solving from Nature
On Permutation Representations for Scheduling Problems
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
New Genetic Local Search Operators for the Traveling Salesman Problem
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
Applying adaptive algorithms to epistatic domains
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 1
Toward minimal restriction of genetic encoding and crossovers for the two-dimensional Euclidean TSP
IEEE Transactions on Evolutionary Computation
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Crossover for evolutionary algorithms applied to permutation problems is a difficult and widely discussed topic. In this paper we use ideas from ant colony optimization to design a new permutation crossover operator. One of the advantages of the new crossover operator is the ease to introduce problem specific heuristic knowledge. Empirical tests on a travelling salesperson problem show that the new crossover operator yields excellent results and significantly outperforms evolutionary algorithms with edge recombination operator as well as pure ant colony optimization.