Comparing carbon dioxide emissions of trucking and intermodal container transport in Taiwan

Liao, Chun Hsiung; Tseng, Po-Hsing; Lu, Chin‐Shan

doi:10.1016/j.trd.2009.05.002

Cited by 93 publications

(64 citation statements)

References 4 publications

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“…Paltsev et al [28] evaluated the US greenhouse gas quota and trading plan and analyzed the Emissions Forecasting and Policy Analysis (EPPA) model. Quota transaction [19,22] CERs [21,23] Certified emission reduction EUAs [24][25][26][27] European Union emission quota AAUs [28] Assigned amount units Program trading [30] VERs [31][32][33][34][35] Voluntary emission reduction VCS [36][37][38] Voluntary carbon standard…”

Section: Supply Chain Model With Carbon Emissionsmentioning

confidence: 99%

“…Ulku et al [29] believed that the combined truck transport model could effectively reduce the transportation cost and CO 2 emission. Liao et al [31] pointed out that replacing combined transport with long-distance truck transport can significantly reduce carbon emissions. In the traditional delivery strategy model, the research on carbon emissions is often overlooked, and cost profit model are generally valued.…”

Section: Supply Chain Model With Carbon Emissionsmentioning

confidence: 99%

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Low-Carbon Planning and Design in B&R Logistics Service: A Case Study of an E-Commerce Big Data Platform in China

Sun

2017

Sustainability

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Abstract:The concept of sustainable development requires us to explore a completeness model of low carbon transport and service in the light of the advancement of changes in world cooperation policy. Various kinds of carbon constraints not only limit emissions of contaminants from E-commerce Enterprise of different countries, but they also ensure the market activity around the Belt and Road, so as to avoid the implementation reducing the company's profits significantly. This paper discusses of the strictest periodic low-carbon constraints_(PLC) and the expansion of the mainstream with three relatively weak attributes-cumulative_(CLC), full cycle_(FCLC), and volatility_(VLC)-taking into account the offline delivery of lead time and the online relationship between supply and demand on the platform. We have established four decision models with different carbon confinement intensities and inferred the impact of more detailed carbon constraints on E-commerce delivery strategies. The appropriate operational decisions, under a wide spectrum of carbon constraints, help e-companies develop scientific delivery plans, and provide some inspiration for the promotion of low carbon economy system construction and environmental significance.

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Section: Supply Chain Model With Carbon Emissionsmentioning

confidence: 99%

Section: Supply Chain Model With Carbon Emissionsmentioning

confidence: 99%

Low-Carbon Planning and Design in B&R Logistics Service: A Case Study of an E-Commerce Big Data Platform in China

Sun

2017

Sustainability

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“…For any given capacity value , its fuzzy membership degree ( ) can be calculated by Equation (2) [18,24]. This function will be further used in the fuzzy simulation in the case study section.…”

Section: Fuzzy Service Capacity: Trapezoidal Fuzzy Numbers Vs Triangmentioning

confidence: 99%

“…It has been widely acknowledged to be a better means of transportation compared with the unimodal transportation in many aspects (e.g., transportation economy and sustainability) [1,2], especially in the long-haul transportation setting. The intermodal routing decision aims at selecting the best routes to move containers from their origins to destinations through an intermodal service network to fulfill customers' transportation demands.…”

Section: Introductionmentioning

confidence: 99%

How Uncertain Information on Service Capacity Influences the Intermodal Routing Decision: A Fuzzy Programming Perspective

et al. 2018

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Capacity uncertainty is a common issue in the transportation planning field. However, few studies discuss the intermodal routing problem with service capacity uncertainty. Based on our previous study on the intermodal routing under deterministic capacity consideration, we systematically explore how service capacity uncertainty influences the intermodal routing decision. First of all, we adopt trapezoidal fuzzy numbers to describe the uncertain information of the service capacity, and further transform the deterministic capacity constraint into a fuzzy chance constraint based on fuzzy credibility measure. We then integrate such fuzzy chance constraint into the mixed-integer linear programming (MILP) model proposed in our previous study to develop a fuzzy chance-constrained programming model. To enable the improved model to be effectively programmed in the standard mathematical programming software and solved by exact solution algorithms, a crisp equivalent linear reformulation of the fuzzy chance constraint is generated. Finally, we modify the empirical case presented in our previous study by replacing the deterministic service capacities with trapezoidal fuzzy ones. Using the modified empirical case, we utilize sensitivity analysis and fuzzy simulation to analyze the influence of service capacity uncertainty on the intermodal routing decision, and summarize some interesting insights that are helpful for decision makers.

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“…Respective advantages of the transportation modes above are integrated in the freight routing planning when adopting multi-modal transportation, and the employment of multimodal transportation freight routes has been empirically proved to be a more cost-effective [13] and eco-friendly (less carbon emissions) [14] way than the uni-modal transportation. However, compared with the uni-modal transportation network, the operating distinction among the transportation modes makes the multi-modal transportation freight routing planning more complicated.…”

Section: Introductionmentioning

confidence: 99%

Optimization Models and Solution Algorithms for Freight Routing Planning Problem in the Multi-Modal Transportation Networks: A Review of the State-of-the-Art

Sun¹,

Lang²,

Wang³

2015

TOCIEJ

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Abstract:With the remarkable development of international trade, global commodity circulation has grown significantly. To accomplish commodity circulation among various regions and countries, multi-modal transportation scheme has been widely adopted by a large number of companies. Meanwhile, according to the relevant statistics, the international logistics costs reach up to approximate 30-50% of the total production cost of the companies 1 . Lowering the transportation costs has become one of the most important sources for a company to raise profits and maintain competitiveness in the global market. Thus, how to optimize freight routes selection to move commodities through the multi-modal transportation network has gained great concern of both the decision makers of the companies and the multi-modal transport operators. In this study, we present a systematical review on the multi-modal transportation freight routing planning problem from the aspects of model formulation and algorithm design. Following contents are covered in this review: (1) distinguishing the formulation characteristics of various optimization models; (2) identifying the optimization models in recent studies according to the formulation characteristics; and (3) discussing the solution approaches that are developed to solve the optimization models, especially the heuristic algorithms.

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Comparing carbon dioxide emissions of trucking and intermodal container transport in Taiwan

Cited by 93 publications

References 4 publications

Low-Carbon Planning and Design in B&R Logistics Service: A Case Study of an E-Commerce Big Data Platform in China

Low-Carbon Planning and Design in B&R Logistics Service: A Case Study of an E-Commerce Big Data Platform in China

How Uncertain Information on Service Capacity Influences the Intermodal Routing Decision: A Fuzzy Programming Perspective

Optimization Models and Solution Algorithms for Freight Routing Planning Problem in the Multi-Modal Transportation Networks: A Review of the State-of-the-Art

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