Yard block assignment, internal truck operations, and berth allocation in container terminals: introducing carbon-footprint minimisation objectives

Karakaş, Serkan; Kırmızı, Mehmet

doi:10.1057/s41278-021-00186-7

Cited by 12 publications

(3 citation statements)

References 28 publications

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“…Deep reinforcement learning has been utilized to minimize empty truck trips, while genetic algorithms and greedy-type heuristics have aided in reducing bottlenecks and pollutant emissions [17,18]. Additionally, the amalgamation of Monte Carlo simulation with linear programming has proven effective in curtailing carbon footprint [19,20].…”

Section: Introductionmentioning

confidence: 99%

Chasing Optimization on Multimodal Transportation System: A Strategic Approach to Minimizing Costs and CO2 Emissions

Derpich,

Duran,

Carrasco

et al. 2024

Preprint

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This study aims to enhance multimodal transportation systems by mitigating CO2 emissions and enhancing operational efficiency. It introduces a novel centralized cargo concentration approach tailored for regions facing geographical challenges. The method proposes for direct transportation of cargo from its loading origin to export ports, bypassing intermediate hubs. The mathematical model determines the most efficient means of transport for each route, factoring in variables like distance, volume, and cargo type. Research results indicate that, in scenarios with a high concentration of cargo, multiple hubs may not be necessary, which could streamline transportation and logistics operations. Modal preferences vary based on regional dynamics and cargo characteristics, with rail and sea transport emerging as preferable options under specific circumstances, surpassing the efficacy of road transport. The proposed model showcases reductions in both logistics costs and CO2 emissions compared to road-centric scenarios. It underscores the strategic integration of diverse transportation modes as pivotal for enhancing efficiency and sustainability. This study furnishes a framework adaptable to optimizing multimodal transportation systems in regions sharing similar geographical and logistical attributes.

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Section: Introductionmentioning

confidence: 99%

Chasing Optimization on Multimodal Transportation System: A Strategic Approach to Minimizing Costs and CO2 Emissions

Derpich,

Duran,

Carrasco

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

Section: Introductionmentioning

confidence: 99%

Pursuing Optimization Using Multimodal Transportation System: A Strategic Approach to Minimizing Costs and CO2 Emissions

Derpich,

Duran,

Carrasco

et al. 2024

JMSE

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The core problem of a multimodal transportation system is integrating various transportation modes into a cohesive, efficient, and user-friendly network. This study introduces a novel centralized load concentration approach for regions facing geographic challenges. The principal aim is improving multimodal transportation systems by mitigating CO2 emissions and improving operational efficiency. This will significantly reduce high logistics costs and the environmental impact caused by greenhouse gas emissions, particularly in land transportation, aligning with the global sustainable development goals and offering a promising path towards a more sustainable future. The proposed method implicates direct cargo transportation from its origin to the export ports without passing through intermediate centers. The mathematical model determines the most efficient means of transportation for each route, considering variables such as distance, volume, and type of cargo. Research results indicate that multiple hubs may not be necessary in scenarios with high freight concentration, which could streamline transportation and logistics operations. The modal preferences vary depending on regional dynamics and cargo characteristics, with rail and sea transport emerging as preferable options in specific circumstances, outperforming road transport. The proposed model shows reductions in logistics costs and CO2 emissions compared to road-focused scenarios. This study provides an adaptable framework for optimizing multimodal transportation systems in regions with similar geographic and logistical attributes. It offers a versatile solution to various contexts and needs. Lastly, the strategic integration of multiple modes of transportation is fundamental to improving efficiency and sustainability.

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“…(2019) included electricity demand and supply uncertainty while X Li, Peng, et al (2019). only included electricity demand uncertainty in their modeling Karakas et al (2021). integrated the yard truck deployment problem and yard container stack allocation and optimized emissions and time.…”

mentioning

confidence: 99%

Optimization for Green Container Shipping: A Review and Future Research Directions

KURTULUŞ

2023

Marine Science and Technology Bulletin

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Maritime freight transportation is one of the least emissions-producing transportation alternatives in terms of transported tonnage per distance. However, it produces a high amount of emissions as around 80% of international freight transportation is conducted through seas and 20% of maritime transportation is conducted through container shipping. This makes it crucial to reduce emissions in container shipping. In this regard, this study reviewed previous studies on the environmental optimization of container shipping and identified various future research directions. The results showed that in the sea segment of environmental optimization of container shipping, decisions which require further attention include resource allocation, emission reduction technology choice, disruption recovery, freight rate optimization, and shipment scheduling. The decisions that require future research in the port segment are related to internal transportation and handing operations in container terminals (i.e., yard crane deployment, yard truck deployment, yard truck scheduling, yard container stack allocation, yard container retrieval), renewable energy source installation, and emission reduction technology choice. Vessel scheduling and speed optimization decisions are the most frequently studied decisions in the sea segment, but they are rarely considered for inland shipping of containers. In the sea-port combined segment of container shipping, future studies are required in quay crane scheduling, vessel scheduling, container route allocation, ship route allocation vessel deployment, and emission reduction technology choice. The least studied decision in the door-to-door segment of container shipping includes hub location-allocation, empty container relocation, ship route allocation, vessel deployment, environmental taxation and subsidy scheme, emissions reduction technology choice, and speed optimization. It was also demonstrated that modeling of future studies should more frequently consider uncertainties and social sustainability parameters.

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Yard block assignment, internal truck operations, and berth allocation in container terminals: introducing carbon-footprint minimisation objectives

Cited by 12 publications

References 28 publications

Chasing Optimization on Multimodal Transportation System: A Strategic Approach to Minimizing Costs and CO2 Emissions

Chasing Optimization on Multimodal Transportation System: A Strategic Approach to Minimizing Costs and CO2 Emissions

Pursuing Optimization Using Multimodal Transportation System: A Strategic Approach to Minimizing Costs and CO2 Emissions

Optimization for Green Container Shipping: A Review and Future Research Directions

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