2012
DOI: 10.1007/s00500-012-0855-z
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A novel two-stage hybrid swarm intelligence optimization algorithm and application

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Cited by 169 publications
(101 citation statements)
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“…A novel two-stage hybrid swarm intelligence optimization algorithm is presented to solve traveling salesman problem [41]. This paper presents a novel two-stage hybrid swarm intelligence optimization algorithm called GA-PSO-ACO algorithm that combines the evolution ideas of the genetic algorithms, particle swarm optimization and ant colony optimization based on the compensation for solving the traveling salesman problem.…”
Section: Related Workmentioning
confidence: 99%
“…A novel two-stage hybrid swarm intelligence optimization algorithm is presented to solve traveling salesman problem [41]. This paper presents a novel two-stage hybrid swarm intelligence optimization algorithm called GA-PSO-ACO algorithm that combines the evolution ideas of the genetic algorithms, particle swarm optimization and ant colony optimization based on the compensation for solving the traveling salesman problem.…”
Section: Related Workmentioning
confidence: 99%
“…Ultimately, most ants are focused on the shortest path from the source. The ACO algorithm has strong robustness, distributed cooperation and so on, it has been widely applied in traveling salesman path optimization, shop scheduling, logistics distribution, data mining, image processing, network communication, and so on [2][3][4][5][6]. The ACO algorithm become one of the most effective algorithms to solve combination optimization problem.…”
Section: Introductionmentioning
confidence: 99%
“…The traditional fault diagnosis technology has a better effect on the analysis of the deep level fault of the complex structure, and the higher ability for the operator. In recent years, with the rapid development of artificial intelligence technology, the fault diagnosis technology is developed from the traditional technology to the intelligent technology [1,2]. The intelligent fault diagnosis technology is a kind of intelligent diagnosis methods based on knowledge processing technology.…”
Section: Introductionmentioning
confidence: 99%