Towards practical `neural' computation for combinatorial optimization problems
AIP Conference Proceedings 151 on Neural Networks for Computing
Solving the k-best traveling salesman problem
Computers and Operations Research - Special issue on the traveling salesman problem
The ant colony optimization meta-heuristic
New ideas in optimization
Memetic algorithms: a short introduction
New ideas in optimization
Local Search in Combinatorial Optimization
Local Search in Combinatorial Optimization
Tabu Search
A Population Based Approach for ACO
Proceedings of the Applications of Evolutionary Computing on EvoWorkshops 2002: EvoCOP, EvoIASP, EvoSTIM/EvoPLAN
Memetic Algorithms and the Fitness Landscape of the Graph Bi-Partitioning Problem
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
On Weight-Biased Mutation for Graph Problems
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
Genetic Local Search Algorithms for the Travelling Salesman Problem
PPSN I Proceedings of the 1st Workshop on Parallel Problem Solving from Nature
Local Optimization and the Traveling Salesman Problem
ICALP '90 Proceedings of the 17th International Colloquium on Automata, Languages and Programming
INFORMS Journal on Computing
Grasp and Path Relinking for 2-Layer Straight Line Crossing Minimization
INFORMS Journal on Computing
Advances in evolutionary computing
Tour Merging via Branch-Decomposition
INFORMS Journal on Computing
Dynamics of Local Search Trajectory in Traveling Salesman Problem
Journal of Heuristics
Multicriteria Optimization
E-SCIENCE '06 Proceedings of the Second IEEE International Conference on e-Science and Grid Computing
Computers and Industrial Engineering
The Traveling Salesman Problem: A Computational Study (Princeton Series in Applied Mathematics)
The Traveling Salesman Problem: A Computational Study (Princeton Series in Applied Mathematics)
Combinatorial Optimization: Theory and Algorithms
Combinatorial Optimization: Theory and Algorithms
GRASP and path relinking for the max-min diversity problem
Computers and Operations Research
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
A parallel multi-start search algorithm for dynamic traveling salesman problem
SEA'11 Proceedings of the 10th international conference on Experimental algorithms
International Journal of Metaheuristics
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This study investigates the properties of the edges in a set of locally optimal tours found by multi-start search algorithm for the traveling salesman problem (TSP). A matrix data structure is used to collect global information about edges from the set of locally optimal tours and to identify globally superior edges for the problem. The properties of these edges are analyzed. Based on these globally superior edges, a solution attractor is formed in the data matrix. The solution attractor is a small region of the solution space, which contains the most promising solutions. Then an exhausted enumeration process searches the solution attractor and outputs all solutions in the attractor, including the globally optimal solution. Using this strategy, this study develops a procedure to tackler a multi-objective TSP. This procedure not only generates a set of Pareto-optimal solutions, but also be able to provide the structural information about each of the solutions that will allow a decision-maker to choose the best compromise solution.