针对农村土地流转形成的大规模土地,提出基于轮盘的启发式搜索(Heuristic search based on roulette,HSBOR)算法和基于最小值的启发式搜索(Heuristic search based on minimum,HSBOM)算法,求解跨区域农机调度问题;构建农机调度模型,设计...针对农村土地流转形成的大规模土地,提出基于轮盘的启发式搜索(Heuristic search based on roulette,HSBOR)算法和基于最小值的启发式搜索(Heuristic search based on minimum,HSBOM)算法,求解跨区域农机调度问题;构建农机调度模型,设计HSBOR和HSBOM算法的核心思想,并通过模拟试验比较HSBOR、HSBOM算法与基于优先级规则的启发式(Heuristic based on priority rules,HBOPR)算法在调度成本、运行效率上的优劣。结果表明,HSBOM算法在调度成本和运行效率上最优。展开更多
Routing problem is a very import problem in the network design. However, with the increasing of the number of vertices, the convergence speed of the conventional method (such as the Dijkstra algorithm) becomes slow. I...Routing problem is a very import problem in the network design. However, with the increasing of the number of vertices, the convergence speed of the conventional method (such as the Dijkstra algorithm) becomes slow. In some services, the accurate shortest path isn't requested. This paper presents a new algorithm for solving this problem based on the tabu search technique. The tabu search algorithm can get the satisfied path with the changing of the iteration times, the tabu period and neighborhood size. Simulation results demonstrate that the proposed method is very efficient for computing the shorted path, especially when the scale of the network is large.展开更多
文摘针对农村土地流转形成的大规模土地,提出基于轮盘的启发式搜索(Heuristic search based on roulette,HSBOR)算法和基于最小值的启发式搜索(Heuristic search based on minimum,HSBOM)算法,求解跨区域农机调度问题;构建农机调度模型,设计HSBOR和HSBOM算法的核心思想,并通过模拟试验比较HSBOR、HSBOM算法与基于优先级规则的启发式(Heuristic based on priority rules,HBOPR)算法在调度成本、运行效率上的优劣。结果表明,HSBOM算法在调度成本和运行效率上最优。
文摘Routing problem is a very import problem in the network design. However, with the increasing of the number of vertices, the convergence speed of the conventional method (such as the Dijkstra algorithm) becomes slow. In some services, the accurate shortest path isn't requested. This paper presents a new algorithm for solving this problem based on the tabu search technique. The tabu search algorithm can get the satisfied path with the changing of the iteration times, the tabu period and neighborhood size. Simulation results demonstrate that the proposed method is very efficient for computing the shorted path, especially when the scale of the network is large.
