Two-Phase Optimization Models for Liner Shipping Network Based on Hub Ports Cooperation: From the Perspective of Supply-Side Reform in China

From the perspective of supply-side reform in China, it is hard for COSCO Shipping, a merged company with a strong shipping capacity, to abandon the container shipping market. Meanwhile, the new company could cooperate with new strategic ports along the Maritime Silk Road in liner service. Against t...

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Main Authors: Jingmiao Zhou, Yuzhe Zhao, Xingwen Niu
Format: Article
Language:English
Published: Hindawi-Wiley 2021-01-01
Series:Journal of Advanced Transportation
Online Access:http://dx.doi.org/10.1155/2021/6639218
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spelling doaj-28e51dbc4fe44a9992cc5adc108df2b02021-04-19T00:05:21ZengHindawi-WileyJournal of Advanced Transportation2042-31952021-01-01202110.1155/2021/6639218Two-Phase Optimization Models for Liner Shipping Network Based on Hub Ports Cooperation: From the Perspective of Supply-Side Reform in ChinaJingmiao Zhou0Yuzhe Zhao1Xingwen Niu2Business SchoolCollaborative Innovation Center for Transport StudiesCollaborative Innovation Center for Transport StudiesFrom the perspective of supply-side reform in China, it is hard for COSCO Shipping, a merged company with a strong shipping capacity, to abandon the container shipping market. Meanwhile, the new company could cooperate with new strategic ports along the Maritime Silk Road in liner service. Against this backdrop, this paper aims to optimize the liner shipping network (LSN) from strategic, tactical, and operational levels and help the merged shipping company adjust its operational measures according to market changes. The optimization towards different levels of decision-making process is a new research of highly practical values. Specifically, this paper created two-phase optimization models for LSN based on the selection of hub ports. In Network Assessment (NA) phase, the LSNs of two types of hub ports selected are designed and assessed on strategic and tactical levels, and the primary and secondary routes are identified; in Network Operation (NO) phase, the “path-based flow” formulations are proposed from the operational level, considering operational measures including demand rejection and flow integration. The models in both phases are mixed-integer linear programming (MILP), but are solved by different tools: CPLEX for the NA phase models and the Genetic Algorithm (GA) for the NO phase models due to the computational complexity of the latter problem. Then, a computational experiment is performed on the LSN of COSCO Shipping on the Persian Gulf trade lane. The results have proved the effectiveness of the methodology and inspired important countermeasures for the merged shipping company.http://dx.doi.org/10.1155/2021/6639218
collection DOAJ
language English
format Article
sources DOAJ
author Jingmiao Zhou
Yuzhe Zhao
Xingwen Niu
spellingShingle Jingmiao Zhou
Yuzhe Zhao
Xingwen Niu
Two-Phase Optimization Models for Liner Shipping Network Based on Hub Ports Cooperation: From the Perspective of Supply-Side Reform in China
Journal of Advanced Transportation
author_facet Jingmiao Zhou
Yuzhe Zhao
Xingwen Niu
author_sort Jingmiao Zhou
title Two-Phase Optimization Models for Liner Shipping Network Based on Hub Ports Cooperation: From the Perspective of Supply-Side Reform in China
title_short Two-Phase Optimization Models for Liner Shipping Network Based on Hub Ports Cooperation: From the Perspective of Supply-Side Reform in China
title_full Two-Phase Optimization Models for Liner Shipping Network Based on Hub Ports Cooperation: From the Perspective of Supply-Side Reform in China
title_fullStr Two-Phase Optimization Models for Liner Shipping Network Based on Hub Ports Cooperation: From the Perspective of Supply-Side Reform in China
title_full_unstemmed Two-Phase Optimization Models for Liner Shipping Network Based on Hub Ports Cooperation: From the Perspective of Supply-Side Reform in China
title_sort two-phase optimization models for liner shipping network based on hub ports cooperation: from the perspective of supply-side reform in china
publisher Hindawi-Wiley
series Journal of Advanced Transportation
issn 2042-3195
publishDate 2021-01-01
description From the perspective of supply-side reform in China, it is hard for COSCO Shipping, a merged company with a strong shipping capacity, to abandon the container shipping market. Meanwhile, the new company could cooperate with new strategic ports along the Maritime Silk Road in liner service. Against this backdrop, this paper aims to optimize the liner shipping network (LSN) from strategic, tactical, and operational levels and help the merged shipping company adjust its operational measures according to market changes. The optimization towards different levels of decision-making process is a new research of highly practical values. Specifically, this paper created two-phase optimization models for LSN based on the selection of hub ports. In Network Assessment (NA) phase, the LSNs of two types of hub ports selected are designed and assessed on strategic and tactical levels, and the primary and secondary routes are identified; in Network Operation (NO) phase, the “path-based flow” formulations are proposed from the operational level, considering operational measures including demand rejection and flow integration. The models in both phases are mixed-integer linear programming (MILP), but are solved by different tools: CPLEX for the NA phase models and the Genetic Algorithm (GA) for the NO phase models due to the computational complexity of the latter problem. Then, a computational experiment is performed on the LSN of COSCO Shipping on the Persian Gulf trade lane. The results have proved the effectiveness of the methodology and inspired important countermeasures for the merged shipping company.
url http://dx.doi.org/10.1155/2021/6639218
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AT yuzhezhao twophaseoptimizationmodelsforlinershippingnetworkbasedonhubportscooperationfromtheperspectiveofsupplysidereforminchina
AT xingwenniu twophaseoptimizationmodelsforlinershippingnetworkbasedonhubportscooperationfromtheperspectiveofsupplysidereforminchina
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