Vehicle routing problem with fuel consumption and carbon emission

Jianghua Zhang, Yingxue Zhao, Weili Xue and Jin Li

International Journal of Production Economics, 2015, vol. 170, issue PA, 234-242

Abstract: In this paper, we study a vehicle routing problem (VRP) with the consideration of fuel consumption and carbon emission. To be specific, we incorporate fuel cost, carbon emission cost, and vehicle usage cost into the traditional VRP problem and establish a low-carbon routing problem model. Based on the route splitting method, we develop an improved tabu search algorithm named RS-TS for solving the model. In the RS-TS algorithm, we introduce a novel route encoding and decoding algorithm named WSS, in which three neighborhood search methods are applied. By numerical studies we show that the RS-TS algorithm is effective with a satisfactory solution and can better reveal the relationships among distance, fuel consumption, travel time, and other parameters. Moreover, we also show that the route and vehicle arrangements based on fuel consumption and carbon emission are both economic and environmentally friendly.

Keywords: Logistics management; Vehicle routing problem; Fuel consumption; Carbon emission; Tabu search algorithm (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (31)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0925527315003692
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:proeco:v:170:y:2015:i:pa:p:234-242

DOI: 10.1016/j.ijpe.2015.09.031

Access Statistics for this article

International Journal of Production Economics is currently edited by Stefan Minner

More articles in International Journal of Production Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().