Optimal subsidy design for shore power usage in ship berthing operations

Shuaian Wang, Jingwen Qi, Gilbert Laporte

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Abstract

Maritime transportation is the backbone of international trade but ships emit a large amount of air pollutants at ports. To encourage ships to use clean energy while berthing at port, subsidies are provided to ship operators that use clean energy and the subsidy amount is generally determined based on subjective judgment. We, therefore, examine the optimal subsidy design for government-operated ports, aiming at balancing the environmental benefits and subsidy expenses. Considering the uncertainty of energy requirements by ships, we build a stochastic optimization model. Taking advantage of the problem structure, we convert the model into a deterministic one by applying sample average approximation and a binomial distribution. The model is then linearized and solved by CPLEX. A series of numerical experiments with realistic parameters are conducted to validate the model and useful managerial insights are obtained.

Original languageEnglish
Pages (from-to)566-580
Number of pages15
JournalNaval Research Logistics
Volume69
Issue number4
Early online date15 Oct 2021
DOIs
Publication statusPublished - 30 Jun 2022

Bibliographical note

Funding Information:
Canadian Natural Sciences and Engineering Research Council, 2015‐06189; National Natural Science Foundation of China, 72071173; 71831008; Research Grants Council of the Hong Kong Special Administrative Region, China, 15201718 Funding information

Funding Information:
This research was supported by the Research Grants Council of the Hong Kong Special Administrative Region, China (Project number 15201718) and the National Natural Science Foundation of China (Grant Nos. 72071173, 71831008). Gilbert Laporte was supported by the Canadian Natural Sciences and Engineering Research Council [grant number 2015‐06189]. Thanks are due to the Editor‐in‐Chief, the Associate Editor, and the referee for their valuable comments.

Funding

Canadian Natural Sciences and Engineering Research Council, 2015‐06189; National Natural Science Foundation of China, 72071173; 71831008; Research Grants Council of the Hong Kong Special Administrative Region, China, 15201718 Funding information This research was supported by the Research Grants Council of the Hong Kong Special Administrative Region, China (Project number 15201718) and the National Natural Science Foundation of China (Grant Nos. 72071173, 71831008). Gilbert Laporte was supported by the Canadian Natural Sciences and Engineering Research Council [grant number 2015‐06189]. Thanks are due to the Editor‐in‐Chief, the Associate Editor, and the referee for their valuable comments.

Keywords

  • binomial distribution
  • chance constraint
  • maritime transportation
  • sample average approximation
  • stochastic problem

ASJC Scopus subject areas

  • Modelling and Simulation
  • Ocean Engineering
  • Management Science and Operations Research

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