A new statistical method of assigning vehicles to delivery areas for CO2 emissions reduction

J.C. Velázquez Martínez, J.C. Fransoo, E.E. Blanco, K.B. Valenzuela

Research output: Contribution to journalArticleScientificpeer-review

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.
Original languageEnglish
Pages (from-to)133-144
Number of pages12
JournalTransportation Research. Part D: Transport and Environment
Volume43
DOIs
Publication statusPublished - 1 Mar 2016

Keywords

  • Transportation CO2 emissions
  • Statistical-mathematical approach
  • Assignment problem

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