Publication Type

Journal Article

Version

Postprint

Publication Date

10-2016

Abstract

Consolidation lies at the heart of the last-mile logistics problem. Urban consolidation centers (UCCs) have been set up to facilitate such consolidation all over the world. To the best of our knowledge, most-if not all-of the UCCs operate on volume-based fixed-rate charges. To achieve environmental sustainability while ensuring economic sustainability in urban logistics, we propose, in this paper, a bicriteria auction mechanism for the automated assignment of last-mile delivery orders to transport resources. We formulate and solve the winner determination problem of the auction as a biobjective programming model. We then present a systematic way to generate the Pareto frontier to characterize the tradeoff between achieving economic and environmental sustainabilities in urban logistics. Finally, we demonstrate that our proposed bicriteria auction produces the solutions that significantly dominate those obtained from the fixed-rate mechanisms. Our sensitivity analysis on the willingness of carriers to participate in the UCC operation reveals that higher willingness is favorable toward achieving greater good for all, if UCC is designed to be nonprofit and self-sustaining.Note to Practitioners-One of the main issues with last-mile logistics is the low utilization of delivery trucks, resulting in unnecessarily large number of trucks carrying out the last-mile delivery. This creates congestion, worsens air pollution, and drives up the cost of the individual carriers. Consolidation of orders can reduce the total number of trucks used to perform the last-mile delivery. This can considerably improve the environmental sustainability around the delivery area and reduce the cost of the individual carrier. Without the proper mechanism, however, such consolidation is often not economically sustainable, requiring the government to continually inject subsidy. To address the issue, we propose, in this paper, a bicriteria auction that considers both the economic and environmental sustainability aspects when performing winner determination. We then present a systematic way to characterize the tradeoff between the two objectives. Finally, we show that our proposal leads to the solutions that dominate those obtained from the commonly used fixed-rate mechanisms.

Keywords

Environmental economics, logistics, multi-agent systems, sustainable development, urban pollution

Discipline

Artificial Intelligence and Robotics | Computer Sciences | Transportation

Research Areas

Intelligent Systems and Decision Analytics

Publication

IEEE Transactions on Automation Science and Engineering

Volume

13

Issue

4

First Page

1471

Last Page

1479

ISSN

1545-5955

Identifier

10.1109/TASE.2016.2563459

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Copyright Owner and License

Authors

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://doi.org/10.1109/TASE.2016.2563459

Share

COinS