Yard truck retrofitting and deployment for hazardous material transportation in green ports

Qian Zhang, Shuaian Wang, Lu Zhen

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

In the design of green ports, the strategic decision on what types of container transportation equipment are appropriate is extremely important. Yard trucks (YTs) are indispensable in container transportation. In this paper, we propose a YT retrofitting and deployment problem that considers hazardous material transportation in green ports. A stochastic mixed-integer programming model is developed to minimize the costs of purchasing, retrofitting, and chartering YTs and the operation costs during the planning horizon. An enhanced Benders decomposition based on a Lagrangian relaxation algorithm is developed to solve the model. We conduct numerical experiments to verify the effectiveness of the proposed algorithms. We find that the larger free carbon emission quotas provided to enterprises by the government are not always an optimum solution. This research also provides suggestions that can inform decisions about YT retrofitting and deployment and that can contribute to the sustainable development of green ports.

Original languageEnglish
JournalAnnals of Operations Research
DOIs
Publication statusAccepted/In press - 2022

Keywords

  • Enhanced Benders decomposition based on Lagrangian relaxation
  • Green ports
  • Stochastic programming
  • Yard truck retrofitting and deployment

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Management Science and Operations Research

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