On the mathematical modeling of green one-to-one pickup and delivery problem with road segmentation

Soysal, Mehmet, Cimen, Mustafa and Demir, Emrah ORCID: https://orcid.org/0000-0002-4726-2556 2018. On the mathematical modeling of green one-to-one pickup and delivery problem with road segmentation. Journal of Cleaner Production 174 , pp. 1664-1678. 10.1016/j.jclepro.2017.11.040

Preview

PDF - Accepted Post-Print Version Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (1MB) | Preview

Abstract

This paper presents a green one-to-one pickup and delivery problem including a set of new features in the domain of green vehicle routing. The objective here is to enhance the traditional models for the one-to-one pickup and delivery problem by considering several important factors, such as explicit fuel consumption (which can be translated into emissions), variable vehicle speed and road categorization (i.e., urban, nonurban). Accordingly, the paper proposes a mixed integer programming model for the problem. A case study from the Netherlands shows the applicability of the model in practice. The numerical analyses show that the investigated factors has a significant impact on operational-level logistics decisions and the selected key performance indicators. The results suggest that the proposed green model can achieve significant savings in terms of total transportation cost. The total cost reduction is found to be (i) 3.03% by the use of explicit fuel consumption estimation, (ii) up to 10.7% by accounting for variable vehicle speed and (iii) up to 10.5% by considering road categorization. As total cost involves explicit energy usage estimation, the proposed model has potential to oer a better support to aid sustainable logistics decision-making process.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Business (Including Economics)
Additional Information:	Released with a Creative Commons Attribution Non-Commercial No Derivatives License (CC BY-NC-ND)
Publisher:	Elsevier
ISSN:	0959-6526
Date of First Compliant Deposit:	11 November 2017
Date of Acceptance:	6 November 2017
Last Modified:	01 Dec 2024 00:00
URI:	https://orca.cardiff.ac.uk/id/eprint/106407

Citation Data

Cited 32 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item