发布时间：

2026-04-16

论文名称：

An effective kernel search and dynamic programming hybrid heuristic for a multimodal transportation planning problem with order consolidation

发表刊物：

Transportation Research Part E: Logistics and Transportation Review

刊物所在地：

American

关键字：

Multimodal transportation，Kernel search，Dynamic programming，Column generation

摘要：

We study a realistic capacitated multimodal transportation planning problem (CMTPP) faced by logistics companies when trying to obtain a cost advantage in a competitive market. This problem simultaneously considers limited vehicle numbers and order consolidation. Given a set of origin–destination transportation orders with a time window, solving the CMTPP involves determining the delivery paths of these orders on a capacitated network as well as selecting the transportation modes used on these paths. Without violating time windows and network capacity constraints, all customers’ requests must be satisfied exactly, with minimum overall logistics costs. The CMTPP is formulated as a mixed binary linear program based on which an effective kernel search and dynamic programming hybrid heuristic (HKSDP) is proposed, which repeatedly generates feasible solutions. A column generation approach is also proposed to provide a lower bound for the problem which is then used to evaluate the performance of the proposed heuristics. Numerical experiments for various sizes of random instances (with at most 300 orders in a network and 20 nodes) are conducted. The results demonstrate the effectiveness of column generation in obtaining a tight lower bound as well as the efficiency of the HKSDP in achieving a high-quality near-optimal solution. The average optimality gap is approximately 1.04%. We also provide a practical application of the proposed HKSDP to a logistics network in inland China.

合写作者：

Zhen Yang

第一作者：

Zhaojin Li

论文类型：

期刊论文

通讯作者：

Ya Liu

学科门类：

管理学

一级学科：

管理科学与工程

文献类型：

J

是否译文：

否

发表时间：

2021-08-01

收录刊物：

SSCI、SCI