Minimizing Carbon Dioxide Emissions Due to Container Handling at Marine Container Terminals via Hybrid Evolutionary Algorithms

Considering a rapidly increasing seaborne trade and drastic climate changes due to emissions, produced by oceangoing vessels and container handling equipment, marine container terminal operators not only have to improve effectiveness of their operations to serve the increasing demand, but also to ac...

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Main Authors: Maxim A. Dulebenets, Ren Moses, Eren E. Ozguven, Arda Vanli
Format: Article
Language:English
Published: IEEE 2017-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/7898425/
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spelling doaj-d024f300f90b465e9f8d9afd94d5dc382021-03-29T20:03:49ZengIEEEIEEE Access2169-35362017-01-0158131814710.1109/ACCESS.2017.26930307898425Minimizing Carbon Dioxide Emissions Due to Container Handling at Marine Container Terminals via Hybrid Evolutionary AlgorithmsMaxim A. Dulebenets0https://orcid.org/0000-0001-8456-9736Ren Moses1Eren E. Ozguven2Arda Vanli3Department of Civil and Environmental Engineering, Florida A&M University-Florida State University, Tallahassee, FL, USADepartment of Civil and Environmental Engineering, Florida A&M University-Florida State University, Tallahassee, FL, USADepartment of Civil and Environmental Engineering, Florida A&M University-Florida State University, Tallahassee, FL, USADepartment of Industrial and Manufacturing Engineering, Florida A&M University-Florida State University, Tallahassee, FL, USAConsidering a rapidly increasing seaborne trade and drastic climate changes due to emissions, produced by oceangoing vessels and container handling equipment, marine container terminal operators not only have to improve effectiveness of their operations to serve the increasing demand, but also to account for the environmental impact associated with the terminal operations. This paper proposes a novel mixed integer mathematical model for the berth scheduling problem, which minimizes the total service cost of vessels, including the total carbon dioxide emission cost due to container handling. The latter pollutant is a primary greenhouse gas that causes global warming. A Hybrid Evolutionary Algorithm, which deploys a set of local search heuristics, is developed to solve the problem. Computational experiments showcase that the optimality gap of the proposed solution algorithm does not exceed 1.61%. It is further shown that the application of additional local search heuristics allows efficient discovery of promising solutions throughout the search process. Results from numerical experiments also indicate that changes in the carbon dioxide emission cost may significantly affect the design of berth schedules. The developed mathematical model and the proposed solution algorithm can thus be adopted as effective planning tools by the marine container terminal operators and improve the environmental sustainability of the terminal operations.https://ieeexplore.ieee.org/document/7898425/Marine container terminalscarbon dioxide emissionsvessel service costevolutionary computationhybrid algorithms
collection DOAJ
language English
format Article
sources DOAJ
author Maxim A. Dulebenets
Ren Moses
Eren E. Ozguven
Arda Vanli
spellingShingle Maxim A. Dulebenets
Ren Moses
Eren E. Ozguven
Arda Vanli
Minimizing Carbon Dioxide Emissions Due to Container Handling at Marine Container Terminals via Hybrid Evolutionary Algorithms
IEEE Access
Marine container terminals
carbon dioxide emissions
vessel service cost
evolutionary computation
hybrid algorithms
author_facet Maxim A. Dulebenets
Ren Moses
Eren E. Ozguven
Arda Vanli
author_sort Maxim A. Dulebenets
title Minimizing Carbon Dioxide Emissions Due to Container Handling at Marine Container Terminals via Hybrid Evolutionary Algorithms
title_short Minimizing Carbon Dioxide Emissions Due to Container Handling at Marine Container Terminals via Hybrid Evolutionary Algorithms
title_full Minimizing Carbon Dioxide Emissions Due to Container Handling at Marine Container Terminals via Hybrid Evolutionary Algorithms
title_fullStr Minimizing Carbon Dioxide Emissions Due to Container Handling at Marine Container Terminals via Hybrid Evolutionary Algorithms
title_full_unstemmed Minimizing Carbon Dioxide Emissions Due to Container Handling at Marine Container Terminals via Hybrid Evolutionary Algorithms
title_sort minimizing carbon dioxide emissions due to container handling at marine container terminals via hybrid evolutionary algorithms
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2017-01-01
description Considering a rapidly increasing seaborne trade and drastic climate changes due to emissions, produced by oceangoing vessels and container handling equipment, marine container terminal operators not only have to improve effectiveness of their operations to serve the increasing demand, but also to account for the environmental impact associated with the terminal operations. This paper proposes a novel mixed integer mathematical model for the berth scheduling problem, which minimizes the total service cost of vessels, including the total carbon dioxide emission cost due to container handling. The latter pollutant is a primary greenhouse gas that causes global warming. A Hybrid Evolutionary Algorithm, which deploys a set of local search heuristics, is developed to solve the problem. Computational experiments showcase that the optimality gap of the proposed solution algorithm does not exceed 1.61%. It is further shown that the application of additional local search heuristics allows efficient discovery of promising solutions throughout the search process. Results from numerical experiments also indicate that changes in the carbon dioxide emission cost may significantly affect the design of berth schedules. The developed mathematical model and the proposed solution algorithm can thus be adopted as effective planning tools by the marine container terminal operators and improve the environmental sustainability of the terminal operations.
topic Marine container terminals
carbon dioxide emissions
vessel service cost
evolutionary computation
hybrid algorithms
url https://ieeexplore.ieee.org/document/7898425/
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