Flocks, herds and schools: A distributed behavioral model
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Local Search in Combinatorial Optimization
Local Search in Combinatorial Optimization
Parameter Selection in Particle Swarm Optimization
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
Particle systems—a technique for modeling a class of fuzzy objects
SIGGRAPH '83 Proceedings of the 10th annual conference on Computer graphics and interactive techniques
Tour Merging via Branch-Decomposition
INFORMS Journal on Computing
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
Exact Solutions to the Traveling Salesperson Problem by a Population-Based Evolutionary Algorithm
EvoCOP '09 Proceedings of the 9th European Conference on Evolutionary Computation in Combinatorial Optimization
A novel set-based particle swarm optimization method for discrete optimization problems
IEEE Transactions on Evolutionary Computation
Honey bees mating optimization algorithm for the Euclidean traveling salesman problem
Information Sciences: an International Journal
Discrete particle swarm optimization for TSP: theoretical results and experimental evaluations
ICAIS'11 Proceedings of the Second international conference on Adaptive and intelligent systems
PSO with path relinking for resource allocation using simulation optimization
Computers and Industrial Engineering
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This paper presents a competitive Particle Swarm Optimization algorithm for the Traveling Salesman Problem, where the velocity operator is based upon local search and path-relinking procedures. The paper proposes two versions of the algorithm, each of them utilizing a distinct local search method. The proposed heuristics are compared with other Particle Swarm Optimization algorithms presented previously for the same problem. The results are also compared with three effective algorithms for the TSP. A computational experiment with benchmark instances is reported. The results show that the method proposed in this paper finds high quality solutions and is comparable with the effective approaches presented for the TSP.