scholarly journals The Inland Container Transportation Problem with Separation Mode Considering Carbon Dioxide Emissions

2021 ◽  
Vol 13 (3) ◽  
pp. 1573
Author(s):  
Wenqing He ◽  
Zhihong Jin ◽  
Ying Huang ◽  
Shida Xu
Keyword(s):  
Carbon Dioxide ◽  
Carbon Dioxide Emissions ◽  
Programming Model ◽  
Mixed Integer ◽  
Container Transportation ◽  
Comparison Result ◽  
Matrix Encoding ◽  
Dimensional Variable ◽  
Task Characteristic ◽  
Excellent Stability

This paper investigates the Inland Container Transportation (ICT) problem with carbon dioxide emissions. The separation mode that the tractor and semi-trailer could be detached and it permits multitasking to reduce fuel and carbon emission costs. A mixed-integer programming model with Full-Empty container integration has been built. An improved ant colony optimization with two-dimensional variable matrix encoding and Infeasible-Arc filtration strategy has been proposed. Numerical experiments with different scales and characteristics are simulated and validated in order to demonstrate the effectiveness of the proposed algorithm. The comparison result indicates the excellent stability for our approach with different task characteristic distribution.

scholarly journals Modeling the Multicommodity Multimodal Routing Problem with Schedule-Based Services and Carbon Dioxide Emission Costs

2015 ◽  
Vol 2015 ◽  
pp. 1-21 ◽  
Author(s):  
Yan Sun ◽  
Maoxiang Lang
Keyword(s):  
Carbon Dioxide ◽  
Carbon Dioxide Emissions ◽  
Transportation Network ◽  
Linearization Method ◽  
Mixed Integer ◽  
Multicommodity Flow ◽  
Routing Problem ◽  
Multimodal Transportation ◽  
Proposed Model ◽  
Freight Routing

We explore a freight routing problem wherein the aim is to assign optimal routes to move commodities through a multimodal transportation network. This problem belongs to the operational level of service network planning. The following formulation characteristics will be comprehensively considered: (1) multicommodity flow routing; (2) a capacitated multimodal transportation network with schedule-based rail services and time-flexible road services; (3) carbon dioxide emissions consideration; and (4) a generalized costs optimum oriented to customer demands. The specific planning of freight routing is thus defined as a capacitated time-sensitive multicommodity multimodal generalized shortest path problem. To solve this problem systematically, we first establish a node-arc-based mixed integer nonlinear programming model that combines the above formulation characteristics in a comprehensive manner. Then, we develop a linearization method to transform the proposed model into a linear one. Finally, a computational experiment from the Chinese inland container export business is presented to demonstrate the feasibility of the model and linearization method. The computational results indicate that implementing the proposed model and linearization method in the mathematical programming software Lingo can effectively solve the large-scale practical multicommodity multimodal transportation routing problem.

scholarly journals Synthesis of Sustainable Carbon Negative Eco-Industrial Parks

2021 ◽  
Vol 9 ◽  
Author(s):  
Elizabeth J. Abraham ◽  
Farah Ramadan ◽  
Dhabia M. Al-Mohannadi
Keyword(s):  
Carbon Dioxide ◽  
Circular Economy ◽  
Carbon Dioxide Emissions ◽  
Carbon Capture ◽  
Carbon Dioxide Emission ◽  
Value Added ◽  
Mixed Integer ◽  
Industrial Parks ◽  
And Storage

Growing climate change concerns in recent years have led to an increased need for carbon dioxide emission reduction. This can be achieved by implementing the concept of circular economy, which promotes the practice of resource conservation, emission minimization, and the maintenance of sustainable revenue streams. A considerable amount of carbon dioxide emissions is a consequence of stationary sources from industrial processes. These emissions can be reduced using carbon capture utilization and storage (CCUS) or reduced at source by using emission free renewable resources. The method developed within this work uses mixed integer linear programming (MILP) to design sustainable clusters that convert seawater (including waste brine), air, and waste carbon dioxide emissions to value-added products with sunlight as the main energy source. In this way, circular economy is employed to minimize fresh resource consumption and maximize material reuse. The potential of this work is demonstrated through a case study, which shows that an industrial park may be profitable while adhering to strict emission and material constraints.

scholarly journals Research on Berth-Quay Crane Joint Scheduling Considering Carbon Emission

2021 ◽  
pp. 1-6
Author(s):  
Rui Yang ◽  
◽  
Junqing Sun
Keyword(s):  
Carbon Emissions ◽  
Carbon Dioxide Emissions ◽  
Carbon Emission ◽  
Programming Model ◽  
Container Terminal ◽  
Optimal Scheduling ◽  
Mixed Integer ◽  
Scheduling Problem ◽  
Scheduling Scheme ◽  
Elite Strategy

With the increasing awareness of environmental protection, all walks of life a are paying more and more attention to the carbon dioxide emissions brought by their own industries. For the container terminal, a large proportion of carbon emissions come from the fuel consumption of vessels. In this paper, the consideration of carbon emissions is added to the original berth quay crane joint scheduling problem, and the constraints such as vessel preference for berths and quay crane interference are added. A dual-objective nonlinear mixed integer programming model is established to minimize carbon emissions and minimize costs. The model is solved by the Non-Dominated Sorting Genetic Algorithm with Elite Strategy, and the optimal scheduling scheme is obtained. Finally, the calculation examples are verified to prove the effectiveness and practicability of the model and algorithm.

scholarly journals An Optimization Approach to the Intermodal Transportation Network in Fruit Cold Chain, Considering Cost, Quality Degradation and Carbon Dioxide Footprint

2018 ◽  
Vol 25 (1) ◽  
pp. 61-69 ◽  
Author(s):  
Qianli Ma ◽  
Wenyuan Wang ◽  
Yun Peng ◽  
Xiangqun Song
Keyword(s):  
Carbon Dioxide ◽  
Programming Model ◽  
Cost Minimization ◽  
Network Planning ◽  
Cold Chain ◽  
Mixed Integer ◽  
Optimization Approach ◽  
Intermodal Transportation ◽  
Quality Degradation ◽  
Trade Offs

AbstractThis model optimizes port hinterland intermodal refrigerated container flows, considering both cost and quality degradation, which is distinctive from the previous literature content in a way that it quantifies the influence of carbon dioxide (CO2) emission in different setting temperature on intermodal network planning. The primary contribution of this paper is that the model is beneficial not only to shippers and customers for the novel service design, but also offer, for policy-makers of the government, insights to develop inland transport infrastructures in consideration of intermodal transportation. The majority of models of multimodal system have been established with an objective of cost minimization for normal commodities. As the food quality is possible to be influenced by varying duration time required for the storage and transportation, and transportation accompanied with refrigeration producing more CO2emission, this paper aims to address cost minimization and quality degradation minimization within the constraint of CO2footprint. To achieve this aim, we put the quality degradation model in a mixed-integer linear programming model used for intermodal network planning for cold chain. The example of Dalian Port and Yingkou Port offer insight into trade-offs between transportation temperature and transport mode considering CO2footprint. Furthermore, the model can offer a useful reference for other regions with the demand for different imported food, which requires an uninterrupted cold chain during the transportation and storage.

scholarly journals Optimization of CCUS Supply Chains for Some European Countries under the Uncertainty

Processes ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 960
Author(s):  
Grazia Leonzio ◽  
Pier Ugo Foscolo ◽  
Edwin Zondervan
Keyword(s):  
Carbon Dioxide ◽  
Stochastic Model ◽  
Supply Chains ◽  
Carbon Dioxide Emissions ◽  
Deterministic Model ◽  
Numerical Models ◽  
Production Costs ◽  
Mixed Integer ◽  
The Uk ◽  
And Storage

This paper develops a two-stage stochastic mixed integer linear programming model to optimize Carbon Capture, Utilization and Storage (CCUS) supply chains in Italy, Germany and the UK. Few works are present in the literature about this topic, thus this paper overcomes this limitation considering carbon supply chains producing different products. The objective of the numerical models is to minimize expected total costs, under the uncertainties of the production costs of carbon-dioxide-based compounds. Once carbon dioxide emissions that should be avoided are fixed, according to environmental protection requirements for each country, the optimal design of these supply chains is obtained finding the distribution of carbon dioxide captured between utilization and storage sections, the amount of different carbon-based products and the best connection between each element inside the system. The expected total costs for the CCUS supply chain of Italy, Germany and the UK are, respectively, 77.3, 98.0 and 1.05 billion€/year (1004, 613 and 164 €/ton CO2 captured). A comparison with the respective deterministic model, analyzed elsewhere, is considered through the evaluation of the Expected Value of Perfect Information (EVPI) and the Value of Stochastic Solution (VSS). The former is 1.29 billion€/year, 0.18 million€/year and 8.31 billion€/year, respectively, for the CCUS of Italy, the UK and Germany. VSS on the other hand is equal to 1.56 billion€/year, 0 €/year and 0.1 billion€/year, respectively, for the frameworks of Italy, the UK and Germany. The results show that the uncertain production cost in the stochastic model does not have a significant effect on the results; thus, in this case, there are few advantages in solving a stochastic model instead of the deterministic one.

scholarly journals Optimization of Gantry Crane Scheduling in Container Sea-Rail Intermodal Transport Yard

2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Tian Luo ◽  
Daofang Chang ◽  
Yinping Gao
Keyword(s):  
Programming Model ◽  
Mixed Integer ◽  
Gantry Crane ◽  
Intermodal Transport ◽  
Container Transportation ◽  
Crane Scheduling ◽  
Flexible Schedule ◽  
The Face ◽  
Loading And Unloading ◽  
Gantry Cranes

In the face of rising container throughput and the tasks associated with collecting and dispatching these containers, contributions to the development of sea-rail intermodal transport are required to improve the capacity of container transportation. According to the characteristics and the requirements of the operation of sea-rail intermodal transport, this paper puts forward a design for the transport yard which facilitates container loading and unloading. Through the establishment of a mixed integer programming model, a flexible schedule for gantry crane operation can be realized, so that, during the planned period, the amount of task overflow in loading and unloading operations and the distance covered by all gantry cranes in the yard is minimized. In addition, a genetic algorithm is designed to solve this model. Finally, a specific example of the loading and unloading of a container train at the sea-rail intermodal transport yard is selected to verify the model and the algorithm. The results show that the algorithm can reasonably schedule the gantry cranes to improve their loading and unloading efficiencies in the sea-rail intermodal transport yard.

Synthesis of Carbon Integration Networks Coupled with Hydrate Suppression and Dehydration Options

2018 ◽  
Vol 13 (4) ◽  
Author(s):  
Rachid Klaimi ◽  
Sabla Y Alnouri ◽  
Dhabia Al-Mohannadi ◽  
Joseph Zeaiter ◽  
Patrick Linke
Keyword(s):  
Carbon Dioxide ◽  
Design Process ◽  
Carbon Dioxide Emissions ◽  
Emission Reduction ◽  
Carbon Capture ◽  
Global Climate ◽  
Carbon Dioxide Emission ◽  
Mixed Integer ◽  
Nonlinear Program ◽  
Industrial Cities

Abstract The excessive increase in carbon dioxide emissions through the past several decades has raised global climate change concerns. As such, environmental policy makers have been looking into the implementation of efficient strategies that would ultimately reduce greenhouse gas (GHG) emission levels, and meet strict emissions targets. As part of a national emission reduction strategy, the reduction of carbon-dioxide emissions from industrial activities has been proven to be very significant. This instigated the need for a systematic carbon integration approach that can yield cost-effective carbon integration networks, while meeting prescribed carbon dioxide emission reduction targets in industrial cities. A novel carbon integration methodology has been previously proposed as a carbon network source-sink mapping approach using a Mixed Integer Nonlinear Program (MINLP), and was found to be very effective to devise emission control strategies in industrial cities. This paper aims to further improve the design process of carbon integration networks, by coupling carbon integration networks with hydrate suppression/moisture removal options. This was found vital for the prevention of any potential hazards that are associated with the transportation of carbon dioxide in pipelines, such as hydrate formation and various corrosion effects, which may result from moisture retention. An extensive analysis of carbon capture, dehydration, inhibition, compression, and transmission options have all been incorporated into the network design process, in the course of determining cost-optimal solutions for carbon dioxide networks. The proposed approach has been illustrated using an industrial city case study.

scholarly journals The Tractor and Semitrailer Routing Considering Carbon Dioxide Emissions

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Hongqi Li ◽  
Yanran Li ◽  
Qiuhong Zhao ◽  
Yue Lu ◽  
Qiang Song
Keyword(s):  
Carbon Dioxide ◽  
Simulated Annealing ◽  
Integer Programming ◽  
Heuristic Algorithm ◽  
Carbon Dioxide Emissions ◽  
Programming Model ◽  
Small Scale ◽  
Scale Problem ◽  
Routing Problem ◽  
Second Stage

The incorporation of the minimization of carbon dioxide (CO2) emissions in the VRP is important to logistics companies. The paper deals with the tractor and semitrailer routing problem with full truckload between any two depots of the network; an integer programming model with the objective of minimizing CO2emissions per ton-kilometer is proposed. A two-stage approach with the same core steps of the simulated annealing (SA) in both stages is designed. The number of tractors is provided in the first stage and the CO2emissions per ton-kilometer are then optimized in the second stage. Computational experiments on small-scale randomly generated instances supported the feasibility and validity of the heuristic algorithm. To a practical-scale problem, the SA algorithm can provide advice on the number of tractors, the routes, and the location of the central depot to realize CO2emissions decrease.

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