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Bi-Objective Combinatorial Optimization Model for Emission Reduction Projects at Container Terminals Considering Investment Amount and Reduction Efficiency

还原(数学) 容器(类型理论) 端口(电路理论) 帕累托原理 温室气体 过程(计算) 投资(军事) 多目标优化 计算机科学 运筹学 工程类 运营管理 数学 法学 机械工程 几何学 政治 政治学 生态学 机器学习 电气工程 生物 操作系统
作者
Ruijia Zhao,Yunting Song,Zhenyu Zhao,Qiang Fu,Ruihao Zhao
出处
期刊:Transportation Research Record [SAGE]
标识
DOI:10.1177/03611981241255364
摘要

Ports play a significant role in socio-economic development. However, the substantial carbon emissions generated during their operation processes pose serious health and environmental risks. Port operations involve a wide array of expensive equipment. With the current technological methods, it is possible to transform higher carbon-emitting equipment into lower carbon-emitting equipment through the implementation of emission reduction projects, thereby effectively reducing the carbon emissions of ports. This paper explores the combinatorial optimization methods in the implementation process of various emission reduction projects at container terminals from the perspective of port managers. Firstly, this paper refines the calculation method of estimating carbon emission reduction efficiency by implementing various emission reduction projects throughout the entire process from ship arrival to the completion of handling operations. Secondly, considering practical factors such as the required investment, emission reduction efficiency, and the impacts on port productivity associated with implementing varied emission reduction projects, a bi-objective combinatorial optimization model for emission reduction projects is formulated, with the objectives of minimizing both carbon emissions and the investment amount. An augmented ε-constraint method is introduced to obtain the Pareto solutions, which representing a series of implementation plans for emission reduction projects under different investment levels. Finally, the concept of the “emission reduction rate” is proposed to identify the optimal scheme from the Pareto solutions. The impacts of government carbon emission requirements, status of implemented emission reduction projects, container throughput, and differences in vehicle types on optimization results are explored, leading to several managerial insights. The optimization method can provide a theoretical basis for port managers to devise investment plans for emission reduction projects.

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