论文标题
HVRP的GRASPXEL具有深度搜索拆分过程
A GRASPxELS with Depth First Search Split Procedure for the HVRP
论文作者
论文摘要
事实证明，通过将巨型旅行分为旅行，在全球框架优化中有效地进行了分裂程序。这是通过在巨型旅行中建造的辅助图内生成最佳最短路径来完成的。 Lacomme等人首次引入了有效的应用。 （2001）在解决电容的电弧路由问题（CARP）的元启发式方法中，第二次用于车辆路由问题（VRP）的方法（2004年）。在另一个步骤中，由于使用与资源管理链接的辅助图的节点上的一系列标签，通过对巨型旅行的启发进行了启发，嵌入了元启发式中的拆分过程已扩展以解决更复杂的路由问题。最近，Duhamel等。 （2010年）根据图在图中生成期间的深度搜索方法定义了一个新的拆分家族。首先，已使用掌握元启发式化的位置路由问题评估了新拆分方法的效率。 Duhamel等。 （2010年）提供了有关此主题的完整数值实验。
Split procedures have been proved to be efficient within global framework optimization for routing problems by splitting giant tour into trips. This is done by generating optimal shortest path within an auxiliary graph built from the giant tour. An efficient application has been introduced for the first time by Lacomme et al. (2001) within a metaheuristic approach to solve the Capacitated Arc Routing Problem (CARP) and second for the Vehicle Routing Problem (VRP) by Prins (2004). In a further step, the Split procedure embedded in metaheuristics has been extended to address more complex routing problems thanks to a heuristic splitting of the giant tour using the generation of labels on the nodes of the auxiliary graph linked to resource management. Lately, Duhamel et al. (2010) defined a new Split family based on a depth first search approach during labels generation in graph. The efficiency of the new split method has been first evaluated in location routing problem with a GRASP metaheuristic. Duhamel et al. (2010) provided full numerical experiments on this topic.
