发布时间：

2026-04-16

DOI码：

10.1109/TITS.2022.3216273

论文名称：

A lagrangian relaxation heuristic for a bi-objective multimodal transportation planning problem

发表刊物：

IEEE transactions on Intelligent Transportation Systems

关键字：

Multimodal transportation, bi-objective optimization, Lagrangian relaxation, volume algorithm.

摘要：

We study a realistic Bi-objective Multimodal Transportation Planning Problem (BMTPP) faced by logistics companies when trying to obtain cost advantages and improve the customer satisfaction in a competitive market. The two objectives considered are: the minimization of total transportation cost and the maximization of service quality. Given a set of transportation orders described by an origin, a destination and a time window, solving BMTPP involves determining the delivery path for each order in a capacitated network as well as selecting the carrier with the best service quality for each edge of the path. The BMTPP is formulated as a novel bi-objective mixed integer linear programming model and an iterative -constraint method is applied to solve it. As the NP-hardness of the single-objective problems derived from BMTPP, a Lagrangian Relaxation (LR) heuristic which can not only provide a near-optimal solution but also a lower bound for each of the single-objective problems is developed. 100 randomly generated instances are tested and the computational results demonstrate the effectiveness of the heuristic in obtaining a tight lower bound and a high-quality near-optimal solution for the derived single-objective problem. Various performance indicators show the high-quality of the Pareto front of the bi-objective problem obtained by the heuristic. We also provide a case study for the proposed LR heuristic in a logistics network in China.

备注：

IEEE transactions on Intelligent Transportation Systems

合写作者：

Haoxun Chen,Kun Jin

第一作者：

Zhaojin Li

论文类型：

期刊论文

通讯作者：

Ya Liu

文献类型：

J

ISSN号：

1524-9050

是否译文：

否

发表时间：

2023-01-01

收录刊物：

SCI、SCI