The guilty net for the traveling salesman problem
Computers and Operations Research - Special issue on neural networks and operations research
Tabu search performance on the symmetric traveling salesman problem
Computers and Operations Research - Special issue: heuristic, genetic and tabu search
Self-organizing maps
Weight-value convergence of the SOM algorithm for discrete input
Neural Computation
Fast, efficient and accurate solutions to the Hamiltonian path problem using neural approaches
Computers and Operations Research
A Branch & Cut Algorithm for the Asymmetric Traveling Salesman Problem with Precedence Constraints
Computational Optimization and Applications
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Understanding and reducing variability of SOM neighbourhood structure
Neural Networks - 2006 Special issue: Advances in self-organizing maps--WSOM'05
A Fast Evolutionary Algorithm for Traveling Salesman Problem
ICNC '07 Proceedings of the Third International Conference on Natural Computation - Volume 04
An Angle-Based Crossover Tabu Search for the Traveling Salesman Problem
ICNC '07 Proceedings of the Third International Conference on Natural Computation - Volume 04
A genetic algorithm-based clustering approach for database partitioning
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
An efficient self-organizing map designed by genetic algorithms for the traveling salesman problem
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A Novel Constructive-Optimizer Neural Network for the Traveling Salesman Problem
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
An argument for abandoning the travelling salesman problem as a neural-network benchmark
IEEE Transactions on Neural Networks
Self organization of a massive document collection
IEEE Transactions on Neural Networks
A Kohonen-like decomposition method for the Euclidean traveling salesman problem-KNIES_DECOMPOSE
IEEE Transactions on Neural Networks
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The paper proposes a novel overall-regional competitive SOM (ORC-SOM) algorithm for solving symmetric Euclidean traveling salesman problems (TSPs). Two novel rules, overall and regional competition rules respectively, are introduced in the ORC-SOM. Overall competition is designed to make winning neuron and its neighborhood neurons less competitive for outlining the tour, and regional competition is designed to make them more competitive for refining the tour, both compared with the standard SOM. An increasing radius with respect to iteration is designed for a smooth transition from more focus on outlining to more focus on refining the tour. Besides topology preservation property and convex-hull property, an additional significant property of an optimal tour for a complex TSP, referred to as infiltration property, is introduced, and the feasibility of the ORC-SOM algorithm on these properties are studied. Computational comparisons with typical SOM-based counterparts on two sets of benchmark TSP instances from TSPLIB demonstrate the superiority of the ORC-SOM in solution quality.