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中国管理科学 ›› 2023, Vol. 31 ›› Issue (8): 184-192.doi: 10.16381/j.cnki.issn1003-207x.2022.2199

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草畜平衡约束下带时间窗的放牧路径规划研究

谷晓燕1,陈亮1,刘倩1,穆梦迪2,吴登生3()   

  1. 1.北京信息科技大学信息管理学院, 北京 100192
    2.墨尔本大学工程学院, 墨尔本 3010
    3.中国科学院科技战略咨询研究院, 北京 100190
  • 收稿日期:2022-10-10 修回日期:2023-06-07 出版日期:2023-08-15 发布日期:2023-08-24
  • 通讯作者: 吴登生 E-mail:wds@casipm.ac.cn
  • 基金资助:
    青海省重点研发与转化项目(2022QY206);青海省科技创新基地项目(2022ZY007)

Research on Grazing Path Planning with Time Window under Grass Livestock Balance Constraints

Xiao-yan GU1,Liang CHEN1,Qian LIU1,Meng-di MU2,Deng-sheng WU3()   

  1. 1.School of Information Management, Beijing Information Science & technology University Beijing 100192, China
    2.Melbourne School of Engineering, University of Melbourne, Melbourne 3010, Australia
    3.Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China
  • Received:2022-10-10 Revised:2023-06-07 Online:2023-08-15 Published:2023-08-24
  • Contact: Deng-sheng WU E-mail:wds@casipm.ac.cn

摘要:

草地资源的自然特征决定了草场载畜量的有限性,一年内只有在特定的时间窗适合放牧,承受不了长期、持续地放牧。不合理的放牧路径规划不仅会导致牲畜采食时间与草场生长周期错配,还会导致草场出现超载、欠载及退化等一系列负面问题。本文在考虑草畜平衡的基础上,提出放牧时间惩罚函数,构建了线性时间窗和指数型时间窗放牧路径规划模型,并设计了改进的遗传算法对模型进行求解。最后以青海省海晏县的牧户为例对模型进行了验证。结果表明,带指数型时间窗的算法能够更快地逼近最优解,且综合考虑三种成本比只考虑单一成本为目标得到的放牧路径总成本更低。改进的遗传算法缩短了求解时间并提高了求解稳定性。本文构建的带时间窗路径规划模型充分考虑了草场的自然属性,优化了牧户放牧路径,提高了牧户对草地资源利用的科学性。

关键词: 草畜平衡, 载畜量, 时间窗, 放牧路径规划

Abstract:

The natural characteristics of grassland resources determine the limited livestock carrying capacity of pasture, which is suitable for grazing only at specific time windows in a year and cannot bear long-term and continuous grazing. The unreasonable grazing path planning will not only lead to the mismatch between livestock feeding time and pasture growth cycle, but also lead to a series of negative problems such as overload, underload and degradation of pasture. In this paper, based on the consideration of grass-livestock balance, the grazing time penalty function is proposed, a linear time window and exponential time window grazing path planning model is constructed, and an improved genetic algorithm is designed to solve the model. Finally, the model is validated with an example of a herding household in Haiyan County, Qinghai Province. The results show that the algorithm with exponential time window can find the optimal solution faster. Furthermore, considering the three cost leads to lower total grazing path costs than focusing on a single cost. The improved genetic algorithm shortens the solution time and improves the stability of the solution. The path planning model with time windows constructed in this paper fully considers the natural attributes of pasture, optimizes the grazing path of herders, and improves the scientific use of pasture resources by herders.

Key words: grass-livestock balance, livestock carrying capacity, time window, grazing path planning

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