Multimodal Transportation Flows in Energy Networks with an Application to Crude Oil Markets

Oke, Jimi; Huppmann, Daniel; Marshall, Max; Poulton, Ricky; Siddiqui, Sauleh

doi:10.1007/s11067-018-9387-0

Cited by 6 publications

(3 citation statements)

References 57 publications

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“…To improve the quality of bulk grain transportation services and reduce wastage during bulk grain transportation, China has enacted the "Management Regulations for Wastage in Bulk Grain Water Transport. Oke et al [21] addressed emissions and leaks during multimodal transportation of crude oil and proposed a dynamic multimodal partial equilibrium model applied to the North American oil transportation market. Basu et al [22]considered the possibility of multimodal crude oil transportation in eastern Canada and assessed the wastage of multimodal crude oil using the linear leakage model for crude oil transportation, finding that multimodal transportation can effectively alleviate crude oil transportation issues in eastern Canada.…”

Section: Literature Reviewmentioning

confidence: 99%

Bulk Cargo Multimodal Transportation on Inland Waterways Considering Transport Wastage

Ai,

Zhang,

Liu

et al. 2023

IEEE Access

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Transportation wastage is inevitable during transportation. With the emergence of container transportation, the transportation wastage generated by most cargo through container transportation has been greatly reduced. However, for products such as grain, oil, and sand transported in bulk, significant transportation wastage still occurs during the process. Under the background of vigorously developing intermodal transportation in the transportation industry, there is still limited research on transportation wastage in bulk intermodal transportation. This study proposes a multi-objective model to determine appropriate transport routes and modes for inland waterway dry bulk transport, minimizing transport time and transport costs considering transport wastage. Using existing machine learning algorithms to predict wastage in multimodal transportation of bulk cargo. The goal is to accurately predict transportation wastage, determine transportation routes and modes. Considering the poor generalization ability of heuristic algorithms, a hyper-heuristic algorithm based on the hypervolume indicator is designed to solve the model, and it is validated through simulation experiments. The analysis results show that the model can effectively reduce the wastage rate during bulk intermodal transportation.INDEX TERMS Bulk cargo multimodal transport, hyper-heuristic, multi-objective optimization, transport wastage.

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Section: Literature Reviewmentioning

confidence: 99%

Bulk Cargo Multimodal Transportation on Inland Waterways Considering Transport Wastage

Ai,

Zhang,

Liu

et al. 2023

IEEE Access

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“…The petrol truck routing problem refers to the process of distributing petrol products from a depot to stations, and this distribution process is the last link in the petroleum industry chain. With the development of modern logistics technology, improving the distribution efficiency and reducing costs have become research topics of interest (Oke et al 2018). Achieving these tasks directly serves the end users and ultimately corresponds to increased enterprise profit.…”

Section: Introductionmentioning

confidence: 99%

A metaheuristic method for the multireturn-to-depot petrol truck routing problem with time windows

et al. 2019

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The petrol truck routing problem is an important part of the petrol supply chain. This study focuses on determining routes for distributing petrol products from a depot to petrol stations with the objective of minimizing the total travel cost and the fixed cost required to use the trucks. We propose a mathematical model that considers petrol trucks returning to a depot multiple times and develop a heuristic algorithm based on a local branch-and-bound search with a tabu list and the Metropolis acceptance criterion. In addition, an approach that accelerates the solution process by adding several valid inequalities is presented. In this study, the trucks are homogeneous and have two compartments, and each truck can execute at most three tasks daily. The sales company arranges the transfer amount and the time windows for each station. The performance of the proposed algorithm is evaluated by comparing its results with the optimal results. In addition, a real-world case of routing petrol trucks in Beijing is studied to demonstrate the effectiveness of the proposed approach.

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“…A rigorous survey of their application is available in [19]. Authors in [1,11,18,28,37,40] use complementarity problems to model markets from a game theoretic perspective [4,44], where the complementarity conditions typically arise between the marginal profit and the quantity produced by the producer.…”

Section: Introductionmentioning

confidence: 99%

Sensitivity and covariance in stochastic complementarity problems with an application to North American natural gas markets

Sankaranarayanan

Feijoo

Siddiqui

2018

European Journal of Operational Research

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We provide an efficient method to approximate the covariance between decision variables and uncertain parameters in solutions to a general class of stochastic nonlinear complementarity problems. We also develop a sensitivity metric to quantify uncertainty propagation by determining the change in the variance of the output due to a change in the variance of an input parameter. The covariance matrix of the solution variables quantifies the uncertainty in the output and pairs correlated variables and parameters. The sensitivity metric helps in identifying the parameters that cause maximum fluctuations in the output. The method developed in this paper optimizes the use of gradients and matrix multiplications which makes it particularly useful for large-scale problems. Having developed this method, we extend the deterministic version of the North American Natural Gas Model (NANGAM), to incorporate effects due to uncertainty in the parameters of the demand function, supply function, infrastructure costs, and investment costs. We then use the sensitivity metrics to identify the parameters that impact the equilibrium the most.

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Multimodal Transportation Flows in Energy Networks with an Application to Crude Oil Markets

Cited by 6 publications

References 57 publications

Bulk Cargo Multimodal Transportation on Inland Waterways Considering Transport Wastage

Bulk Cargo Multimodal Transportation on Inland Waterways Considering Transport Wastage

A metaheuristic method for the multireturn-to-depot petrol truck routing problem with time windows

Sensitivity and covariance in stochastic complementarity problems with an application to North American natural gas markets

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