A new statistical method of assigning vehicles to delivery areas for CO2 emissions reduction. (March 2016)

• Record Type: Journal Article
• Authors: Velázquez-Martínez, Josué C.; Fransoo, Jan C.; Blanco, Edgar E.; Valenzuela-Ocaña, Karla B.
• Is Part Of: Transportation research. Volume 43(2016)
• Page Start: 133
• Page End: 144
• Publication Date: 2016-03
• Subjects: Transportation CO2 emissions -- Statistical–mathematical approach -- Assignment problem; Transportation -- Research -- Periodicals; Transportation -- Environmental aspects -- Periodicals; 354.76
• DOI: 10.1016/j.trd.2015.12.009
• Languages: English
• ISSNs: 1361-9209

Abstract

Highlights: We study the impact of road and vehicle conditions on CO2 emissions. The assignment of vehicles to delivery regions affects transportation CO2 emissions. We propose a methodology that minimizes CO2 emissions by assigning trucks to delivery areas. We exemplify our approach for a parcel company in Mexico City. Our methodology obtains savings up to 40 tons of CO2 for the practical case. Abstract: Transportation CO2 emissions are expected to increase in the following decades, and thus, new and better alternatives to reduce emissions are needed. Road transport emissions are explained by different factors, such as the type of vehicle, delivery operation and driving style. Because different cities may have conditions that are characterized by diversity in landforms, congestion, driving styles, etc., the importance of assigning the proper vehicle to serve a particular region within the city provides alternatives to reduce CO2 emissions. In this article, we propose a new methodology that results in assigning trucks to deliver in areas such that the CO2 emissions are minimized. Our methodology clusters the delivery areas based on the performance of the vehicle fleet by using the k -means algorithm and Tukey's method. The output is then used to define the optimal CO2 truck-area assignment. We illustrate the proposed approach for a parcel company that operates in Mexico City and demonstrate that it is a practical alternative to reduce transportation CO2 emissions by matching vehicle type with delivery areas.