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The performance research on solvingTSPby four typicalAI algorithms

Yue Wu, Zheng-qiang Jiang


Travelling Salesmen Problem(VRP) has an important theoretical value and practical significance inmathematical and logistics field. ItÂÂ’s a typical NPHard problem, and artificial intelligent (AI) Algorithm has been already proven to be a very effect way in solving this problem. This paper carried out the performance research on solving TSP by four typicalAI algorithms after in-depth analyzed the TSP and these four algorithms (genetic algorithm, particle swarmoptimization algorithm, simulated annealing algorithmand ant colony algorithm). This paper verified the TSP solving performance by China travelling salesmen problem experiments and MATLAB programming. The results showed that: considering the average iteration time, SA < PSO< ACA


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  • キャス
  • Google スカラー
  • Jゲートを開ã
  • 中国国家知識基盤 (CNKI)
  • サイテファクター
  • コスモスIF
  • 研究ジャーナル索引作æˆãƒ‡ã‚£ãƒ¬ã‚¯ãƒˆãƒª (DRJI)
  • 秘密検索エンジン研究所
  • 学術論文インパクトファクター (SAJI))
  • ICMJE

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