Suppr超能文献

一种基于温度时间窗的危险货物车辆路径优化新方法。

A novel optimization method for hazardous materials vehicle routing with temperature-based time windows.

作者信息

Ding Lu, Zhang Fangwei, Ye Jun, Kong Fanyi, Jiao Minhui

机构信息

School of Navigation and Shipping, Shandong Jiaotong University, Weihai, Shandong, China.

School of International Business, Shandong Jiaotong University, Weihai, Shandong, China.

出版信息

PeerJ Comput Sci. 2024 Dec 13;10:e2586. doi: 10.7717/peerj-cs.2586. eCollection 2024.

Abstract

As a concrete achievement of sharing economy, sharing intermediate bulk containers (IBCs) have emerged and developed in recent years. Meanwhile, high temperature is one of the essential factors in routing optimal problems for vehicles with hazardous material (hazmat). Therefore, to address the above issue, a variant of the hazmat vehicle routing problem of sharing IBCs is proposed. Correspondingly, a mixed non-linear integer programming model is refined considering temperature-based time windows. Specifically, the given problem is solved by using a novel adaptive large neighborhood search (ALNS) algorithm. The main innovation points are as follows. Firstly, temperature-based time windows are quantified and integrated into the proposed hazmat vehicle routing optimal model. Secondly, novel heuristic operators are introduced in the ALNS algorithm. Finally, 18 numerical examples for the Solomon set demonstrate that the proposed algorithm is suitable to solve this kind of hazmat vehicle routing optimal problem.

摘要

作为共享经济的一项具体成果,共享中型散装容器(IBC)近年来应运而生并得到发展。同时,高温是危险物品运输车辆路径优化问题的关键因素之一。因此,为解决上述问题,提出了一种共享IBC的危险物品运输车辆路径问题的变体。相应地,考虑基于温度的时间窗,改进了一个混合非线性整数规划模型。具体而言,通过使用一种新颖的自适应大邻域搜索(ALNS)算法来求解给定问题。主要创新点如下。首先,对基于温度的时间窗进行量化并将其纳入所提出的危险物品运输车辆路径优化模型。其次,在ALNS算法中引入了新颖的启发式算子。最后,针对所罗门数据集的18个数值例子表明,所提出的算法适用于解决此类危险物品运输车辆路径优化问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa9a/11784799/c882c4421e23/peerj-cs-10-2586-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验