Open Access Repository

Berth allocation and quay crane assignment for the trade-off between service efficiency and operating cost considering carbon emission taxation

Downloads

Downloads per month over past year

Wang, T, Du, Y ORCID: 0000-0001-7540-493X, Fang, D and Li, Z 2020 , 'Berth allocation and quay crane assignment for the trade-off between service efficiency and operating cost considering carbon emission taxation' , Transportation Science , doi: 10.1287/trsc.2019.0946.

[img]
Preview
PDF (Author's accepted manuscript)
139689 - Berth ...pdf | Download (853kB)

| Preview

Abstract

To sustain the development of maritime transportation, “green ports,” which operate with a good balance between environmental impact and economic interests, have been the focus of port operators and government agencies and are required to look into energy saving and emission reduction initiatives. One such reduction strategy proposed by the International Maritime Organization suggested imposing a carbon emission tax on ports as a long-term solution to reduce carbon emissions, but this would definitely increase the operating cost of ports. Quay cranes (QCs), as one type of handling equipment, play an important role in the service efficiency and carbon emission of ports. Therefore, this paper makes an effort to explore the study of the integrated berth allocation and QC assignment problem with the consideration of carbon emission taxation. This problem is formulated as a biobjective integer programming model, aimed at minimizing the total completion delay of all tasks and the total operating costs for all QCs. Finally, numerical experiments are performed to assess the applicability of the proposed models and evaluate the efficiency of the developed solution algorithm.

Item Type: Article
Authors/Creators:Wang, T and Du, Y and Fang, D and Li, Z
Keywords: OR in maritime industry, berth allocation and quay crane assignment, carbon emission taxation, biobjective integer programming, balanced box method
Journal or Publication Title: Transportation Science
Publisher: Inst Operations Research Management Sciences
ISSN: 0041-1655
DOI / ID Number: 10.1287/trsc.2019.0946
Copyright Information:

Copyright 2020 INFORMS

Related URLs:
Item Statistics: View statistics for this item

Actions (login required)

Item Control Page Item Control Page
TOP