Application of ant colony genetic hybrid algorithm in Enshi route planning

Xian Fu; Ruiwen Ye; Ruogu Zhang; Ziyi Li; NingNing Zhang; Sisi Dong; Ting Ren; Weiqi Zhou; Shicheng Zhou

doi:10.1117/12.2686421

10 August 2023 Application of ant colony genetic hybrid algorithm in Enshi route planning

Xian Fu, Ruiwen Ye, Ruogu Zhang, Ziyi Li, NingNing Zhang, Sisi Dong, Ting Ren, Weiqi Zhou, Shicheng Zhou

Proceedings Volume 12759, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2023); 127591H (2023) https://doi.org/10.1117/12.2686421
Event: 2023 3rd International Conference on Automation Control, Algorithm and Intelligent Bionics (ACAIB 2023), 2023, Xiamen, China

Abstract

Choosing the optimum route is the most critical planning content in economic tourism planning. This paper takes the coordinates of tourism attractions in Enshi as the research background, considers the problem of travel route planning as a tourism salesman problem, and solves the shortest circuit path for traveling salesman as the research object. In our research, we chose the genetic algorithm, the Ant Colony Algorithm, and the combination of the two algorithms and compared and analyzed them with the best parameters. The experiment shows that combining the ant colony and genetic algorithms can more effectively find the shortest circuit path in developing tourism planning in the Enshi Scenic Area. At the same time, the effect is obviously better than the results obtained by any of the algorithms alone.

Citation Download Citation

Xian Fu, Ruiwen Ye, Ruogu Zhang, Ziyi Li, NingNing Zhang, Sisi Dong, Ting Ren, Weiqi Zhou, and Shicheng Zhou "Application of ant colony genetic hybrid algorithm in Enshi route planning", Proc. SPIE 12759, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2023), 127591H (10 August 2023); https://doi.org/10.1117/12.2686421

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