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
Proceedings of the third international conference on Genetic algorithms
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
The Design of Innovation: Lessons from and for Competent Genetic Algorithms
The Design of Innovation: Lessons from and for Competent Genetic Algorithms
A Survey of Optimization by Building and Using Probabilistic Models
Computational Optimization and Applications
Finding Multimodal Solutions Using Restricted Tournament Selection
Proceedings of the 6th International Conference on Genetic Algorithms
Permutation Optimization by Iterated Estimation of Random Keys Marginal Product Factorizations
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
From Recombination of Genes to the Estimation of Distributions I. Binary Parameters
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
Efficient cluster compensation for lin-kernighan heuristics
Efficient cluster compensation for lin-kernighan heuristics
Bayesian optimization algorithm: from single level to hierarchy
Bayesian optimization algorithm: from single level to hierarchy
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Effects of a deterministic hill climber on hBOA
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Effects of discrete hill climbing on model building forestimation of distribution algorithms
Proceedings of the 15th annual conference on Genetic and evolutionary computation
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A basic scheme for solving permutation problems in the framework of probabilistic model-building genetic algorithms (PMBGAs) that uses edge histogram based sampling techniques was reported in [23]. Two sampling algorithms - sampling without template, and the sampling with template were presented. In this paper, we combine local search heuristics with those sampling algorithms to solve the traveling salesman problem (TSP). We tested two types of heuristics; one is a simple heuristic called 2-OPT, and the other is a sophisticated Lin-Kernighan heuristic. The results show that edge histogram based sampling with these heuristics improve the performance significantly, and can solve large problems having thousands of cities fairly well. The algorithm is thus seen to be scalable.