Research on Traversal Path Planning and Collaborative Scheduling for Corn Harvesting and Transportation in Hilly Areas Based on Dijkstra’s Algorithm and Improved Harris Hawk Optimization

Huanyu Liu, Jiahao Luo, Lihan Zhang, Hao Yu, Xiangnan Liu and Shuang Wang ()
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Huanyu Liu: Institute of Modern Agricultural Equipment, Xihua University, Chengdu 610039, China
Jiahao Luo: Institute of Modern Agricultural Equipment, Xihua University, Chengdu 610039, China
Lihan Zhang: Institute of Modern Agricultural Equipment, Xihua University, Chengdu 610039, China
Hao Yu: Institute of Modern Agricultural Equipment, Xihua University, Chengdu 610039, China
Xiangnan Liu: Institute of Modern Agricultural Equipment, Xihua University, Chengdu 610039, China
Shuang Wang: Institute of Modern Agricultural Equipment, Xihua University, Chengdu 610039, China

Agriculture, 2025, vol. 15, issue 3, 1-33

Abstract: This study addresses the challenges of long traversal paths, low efficiency, high fuel consumption, and costs in the collaborative harvesting of corn by harvesters and grain transport vehicles in hilly areas. A path-planning and collaborative scheduling method is proposed, combining Dijkstra’s algorithm with the Improved Harris Hawk Optimization (IHHO) algorithm. A field model based on Digital Elevation Model (DEM) data is created for full coverage path planning, reducing traversal path length. A field transfer road network is established, and Dijkstra’s algorithm is used to calculate distances between fields. A multi-objective collaborative scheduling model is then developed to minimize fuel consumption, scheduling costs, and time. The IHHO algorithm enhances search performance by introducing quantum initialization to improve the initial population, integrating the slime mold algorithm for better exploration, and applying an average differential mutation strategy and nonlinear energy factor updates to strengthen both global and local search. Non-dominated sorting and crowding distance techniques are incorporated to enhance solution diversity and quality. The results show that compared to traditional HHO and HHO algorithms, the IHHO algorithm reduces average scheduling costs by 4.2% and 14.5%, scheduling time by 4.5% and 8.1%, and fuel consumption by 3.5% and 3.2%, respectively. This approach effectively reduces transfer path costs, saves energy, and improves operational efficiency, providing valuable insights for path planning and collaborative scheduling in multi-field harvesting and transportation in hilly areas.

Keywords: traversal path planning; collaborative scheduling; corn harvesting and transportation; Dijkstra’s algorithm; improved Harris hawk optimization algorithm; hilly areas (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2025
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