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Annals of Advanced Agricultural Sciences
AS > Volume 3, Number 2, May 2019

Solution of TSP Problem of Measurement of Soil Attributes for Precision Agriculture

Download PDF  (989.7 KB)PP. 14-20,  Pub. Date:May 28, 2019
DOI: 10.22606/as.2019.32002

Author(s)
Zehui Yun, Shiquan Shao, Tongning Mai
Affiliation(s)
College of Electrical & Information Engineering, Southwest Minzu University, Chengdu, China
College of Electrical & Information Engineering, Southwest Minzu University, Chengdu, China
College of Electrical & Information Engineering, Southwest Minzu University, Chengdu, China
Abstract
There are many PATCHES in the measurement of soil attributes in precision agriculture, which are greatly different from the surrounding soil attributes. In this paper, firstly, we build a TSP model of precision agriculture based on the location of PATCHES. Then, we use the improved ant colony algorithm to solve the TSP model. Numerical simulations show the effectiveness and reliability of the proposed method.
Keywords
Precision agriculture, TSP problem, ant colony algorithm
References
  • [1]  LI Chengbing, GUO Ruixue, LI Min. Application of improved ant colony algorithm in travelling salesman problem[J]. Journal of Computer Applications,2014(z1).
  • [2]  Wang Peidong, Tang Gongyou, Yang Xixin, et al. An Improved Ant Colony Algorithm for Traveling Salesman Problems [J]. Periodical of Ocean University of China, 2013, 43(1):93-97.
  • [3]  Yang Xuefeng. Ant Colony Algorithm for TSP Problem [D]. Jilin University,2010.
  • [4]  Xu Kaibo. Improvement of Ant Colony Optimization Algorithm and Its Applications in Several Optimization Problems [D]. Jiangnan University,2018.
  • [5]  YU Ying-ying, CHEN Yan, LI Tao-ying, et al. Improved genetic algorithm for solving TSP [J]. Control and Decision,2014(8).
  • [6]  SHEN Xuanjing, LIU Yong-yang, HUANG Yong-ping. Fast ant colony algorithm for solving traveling salesman problem[J]. Journal of Jilin University (Engineering and Technology Edition),2013,43(01):147-151.
  • [7]  WANG Jianwen, DAI Guang-ming, XIE Bai-qiao, ZHANG Quan-yuan. A survey of solving the traveling salesman problem[J]. Computer Engineering & Science,2008(02):72-74+155.
  • [8]  Dorigo M, Maniezzo V, Colorni A. The Ant System: Optimization by a Colony of Cooperating Agents[J].IEEE Transon Systems, Man, and Cybernetics Part B,1996,26(1):29-41.
  • [9]  Dorigo M, Gambardella L M. A Study of Some Properties of Ant-Q[C]∥ Proc of the 44th Int’l Conf on Parallel Problem Solving from Nature,1996: 656-665.
  • [10]  Thayer T C, Vougioukas S, Goldberg K, et al. Routing Algorithms for Robot Assisted Precision Irrigation[C]. international conference on robotics and automation, 2018: 2221-2228.
  • [11]  Tokekar P, Hook J V, Mulla D, et al. Sensor planning for a symbiotic UAV and UGV system for precision agriculture[C]// Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International Conference on. IEEE, 2013.
  • [12]  Aspects of Precision Agriculture S. T. Jawaid and S. L. Smith, “Informative path planning as a maximum traveling salesman problem with submodular rewards,” Discrete Appl. Math., vol. 186, pp. 112–127, 2015.
  • [13]  T. H. Pham, Y. Bestaoui and S. Mammar, "Aerial robot coverage path planning approach with concave obstacles in precision agriculture," 2017 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED-UAS), Linkoping, 2017, pp. 43-48.
  • [14]  Zhou K, Leck Jensen A, S Rensen C G, et al. Agricultural operations planning in fields with multiple obstacle areas[J]. Computers and Electronics in Agriculture, 2014, 109:12-22.
  • [15]  Han Yu. Study on genetic algorithm for travel salesman problem[D]. Southwest Jiaotong University,2006.
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