Multimodal Transportation Route Optimization of Cold Chain Container in Time-Varying Network Considering Carbon Emissions

Liu, Shouchen

doi:10.3390/su15054435

Cited by 16 publications

(7 citation statements)

References 4 publications

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“…Concurrently, [23] delves into the intricacies of the agricultural logistics chain in China, revealing that road congestion contributes to a carbon emission surge of over 20%, thus advocating for route optimization for cold chain containers to mitigate such adverse impacts.…”

Section: Of 18mentioning

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: Of 18mentioning

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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“…Carbon emission cost refers to the cold chain lowcarbon logistics and distribution process, vehicle driving fuel consumption and consumption of refrigerant will produce carbon dioxide, and the fuel consumption is related to the vehicle weight and travelling distance [22]. The formula for calculating the carbon emission cost of vehicle travelling fuel consumption is as follows:…”

Section: Cost Of Carbon Emissionsmentioning

confidence: 99%

Cold Chain Low-carbon Logistics Path Optimisation Method Based on Improved Hummingbird Optimisation Algorithm

Long

2024

EAI Endorsed Trans Energy Web

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INTRODUCTION:The research of scientific and reasonable logistics and distribution programme time the pursuit of each logistics enterprise, not only can improve customer satisfaction and corporate image, but also help to reduce distribution costs. OBJECTIVES: For the current cold chain low-carbon logistics distribution path optimisation methods there are problems such as easy to fall into the local optimum, optimisation time-consuming. METHODS: This paper proposes a cold chain low-carbon logistics distribution path optimisation method based on the improved Hummingbird optimisation algorithm. Firstly, by analyzing the characteristics of the cold chain low-carbon logistics distribution path optimization problem, designing the cold chain low-carbon logistics path optimization objective function and constraints, and constructing a cold chain low-carbon logistics distribution path optimization model based on a soft time window; then, the hummingbird optimization algorithm is improved by using the initialization strategy of the set of good points and the cardinality leap strategy, to overcome the defects of the hummingbird optimization algorithm; secondly, a method based on intelligent optimization algorithm is proposed by designing the double-layer array coding and the adaptive function, combined with the improved hummingbird optimization algorithm. A cold chain low-carbon logistics path optimization method based on intelligent optimization algorithm is proposed; finally, the superiority and robustness of the proposed method are verified by simulation experimental analysis. RESULTS: The results show that the proposed method not only improves the optimisation time, but also increases the optimisation fitness value. CONCLUSION: This paper solves the problem that the optimisation of the green low-carbon logistics path optimisation problem is time-consuming and prone to falling into local optimum.

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“…Robust optimization with uncertain demand will increase the total cost of low-carbon multimodal transport due to the pursuit of stability, and the impact of time uncertainty on the total cost is significant and fuzzy. Liu et al [17] mainly studied the transportation route optimization of cold chain containers in multimodal transport systems, and built an optimization model with the sum of carbon emission cost, transportation cost, time window penalty cost, and cold chain cargo damage cost as the objective function. In addition, the Hummingbird Evolutionary Genetic Algorithm was adopted as a solution tool, and it was found that the optimized multimodal transport route could significantly reduce carbon emissions, thereby reducing the impact on the environment.…”

Section: Research On Multimodal Transport Multiparty Collaborationmentioning

confidence: 99%

Research on Multimodal Transport of Electronic Documents Based on Blockchain

Qian,

Shen,

Yang

et al. 2024

BDCC

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Multimodal transport document collaboration is the foundation of multimodal transport operations. Blockchain technology can effectively address issues such as a lack of trust and difficulties in information sharing in current multimodal transport document collaboration. However, in current research on blockchain-based electronic documents, the bottleneck lies in the collaboration aspect of multimodal transport among multiple entities, known as the “one-bill coverage system” collaborative problem. The collaboration problem studied in this paper involves selecting suitable transport routes according to the shipper’s transport needs, and selecting the most suitable specific carrier from numerous carriers. To address the collaboration problem among multiple parties in the multimodal transport “one-bill coverage system”, a multiparty collaboration mechanism is designed. This mechanism includes two aspects: firstly, designing the architecture of the multimodal transport blockchain transport platform, which reengineers the operation process of the “one-bill coverage system” for container multimodal transport; secondly, constructing a multiparty collaboration decision-making model for the “one-bill coverage system” in multimodal transport. The model is solved and analyzed, and the collaboration strategy obtained is embedded in the application layer of the platform. Smart contracts related to the “one-bill coverage system” for multimodal transport are written in the Solidity language and deployed and executed on the Remix platform. The design of this mechanism can effectively improve the collaboration efficiency of participants in the “one-bill coverage system” for multimodal transport.

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Multimodal Transportation Route Optimization of Cold Chain Container in Time-Varying Network Considering Carbon Emissions

Cited by 16 publications

References 4 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

Cold Chain Low-carbon Logistics Path Optimisation Method Based on Improved Hummingbird Optimisation Algorithm

Research on Multimodal Transport of Electronic Documents Based on Blockchain

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