ass日本风韵熟妇pics男人扒开女人屁屁桶到爽|扒开胸露出奶头亲吻视频|邻居少妇的诱惑|人人妻在线播放|日日摸夜夜摸狠狠摸婷婷|制服 丝袜 人妻|激情熟妇中文字幕|看黄色欧美特一级|日本av人妻系列|高潮对白av,丰满岳妇乱熟妇之荡,日本丰满熟妇乱又伦,日韩欧美一区二区三区在线

In recent years, the rapid advancement of smart agriculture has spurred the pursuit of higher real-time scheduling for inter-connected agricultural machinery across multiple regions. This approach aims to achieve more reasonable allocation of agricultural machinery resources. Cross-regional agricultural machinery operations have emerged as the principal service mode for completing the tasks of the “three summer” harvest. Drawing from real-world scenarios of cross-regional wheat harvesting machinery operations, the cross-regional scheduling problem involving multiple depots and machinery types was investigated, incorporating time windows. Economic and environmental costs were simultaneously considered, leading to the establishment of a cross-regional scheduling model with the objective of minimizing scheduling costs. Tailored to the characteristics of the problem, a genetic algorithm variable neighborhood search (GAVNS) was designed. This algorithm enhanced efficiency and flexibility in solution search through operations like crossover, random perturbations, and adaptive neighborhood selection. The operational demands of 72 wheat-producing counties in the Huang-Huai-Hai Plain in China were computed and analyzed. Comparative analysis revealed that the proposed algorithm outperformed alternative algorithms in terms of reduced iteration count to reach the optimal solution and faster convergence speed, with 16.41% decrease compared with the genetic algorithm and 11.15% decrease compared with the variable neighborhood search algorithm in terms of the objective function value. Furthermore, different scheduling modes were compared, highlighting the open path mode as more conducive to enhancing crossregional scheduling service efficiency, leading to 17.76% reduction in scheduling costs compared with the closed path mode.