Column-and-constraint-generation-based approach to a robust reverse logistic network design for bike sharing

Huang, Sen; Liu, Kanglin; Zhang, Zhi‐Hai

doi:10.1016/j.trb.2023.04.010

Cited by 7 publications

(2 citation statements)

References 64 publications

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“…Aiming at the above two-stage robust optimization model, this study used the column constraint generation algorithm (C&CG) to solve it [32,33]. The C&CG divides the established model into the main problem and sub-problem for iterative solutions.…”

Section: Model Solving Methodsmentioning

confidence: 99%

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Low-Carbon-Oriented Capacity Optimization Method for Electric–Thermal Integrated Energy System Considering Construction Time Sequence and Uncertainty

Wang,

Zhao,

Huang

2024

Processes

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The interdependence of various energy forms and flexible cooperative operation between different units in an integrated energy system (IES) are essential for carbon emission reduction. To address the planning problem of an electric–thermal integrated energy system under low-carbon conditions and to fully consider the low carbon and construction sequence of the integrated energy system, a low-carbon-oriented capacity optimization method for the electric–thermal integrated energy system that considers construction time sequence (CTS) and uncertainty is proposed. A calculation model for the carbon transaction cost under the ladder carbon trading mechanism was constructed, and a multi-stage planning model of the integrated energy system was established with the minimum life cycle cost, considering carbon transaction cost as the objective function, to make the optimal decision on equipment configuration in each planning stage. Finally, a case study was considered to verify the advantages of the proposed capacity optimization method in terms of economy and environmental friendliness through a comparative analysis of different planning cases. Simulation results show that, compared with the scenario of completing planning at the beginning of the life cycle at one time, the proposed low-carbon-oriented capacity optimization method that considers construction time sequence and uncertainty can not only reduce the cost of the integrated energy system, but also help to enhance renewable energy utilization and reduce the system’s carbon emissions; the total cost of phased planning is reduced by 11.91% compared to the total cost of one-time planning at the beginning of the year.

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Section: Model Solving Methodsmentioning

confidence: 99%

“…After the derivation and transformation, the two-stage robust model is decoupled into a central problem (Formula (44)) and a sub-problem (Formula (45)) with a relaxed integer linear form. The transformed model can be solved using the C&CG algorithm [32,33] as follows:…”

Section: Model Solving Methodsmentioning

confidence: 99%