In practice, the scheduling of gas and oil pipeline networks is a continuous and dynamic process with a large number of uncertainties. Therefore, shorter calculation time and solution quality are always important indicators to measure the practicability of solution methods, especially in the real-time and active pipeline scheduling. The emergence of digital and intelligent technologies makes the data sensing and decision-making possible to be real-time and continuous. This chapter summarizes existing research from the perspective of modeling methods and solution algorithms, so as to provide the research basis and research direction for intelligent scheduling of pipeline networks. The modeling methods are mainly divided into mathematical programming, generalized disjunctive programming (GDP), and resource task network (RTN). The solution algorithms include mathematical programming, heuristic algorithm, metaheuristic algorithm, dynamic programming algorithm, and data-driven algorithm.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Advanced Modeling and Algorithm for Pipeline Scheduling


    Contributors:
    Su, Huai (editor) / Liao, Qi (editor) / Zhang, Haoran (editor) / Zio, Enrico (editor) / Xu, Ning (author) / Zhang, Bo (author)

    Published in:

    Publication date :

    2023-12-13


    Size :

    14 pages




    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




    Overview for Pipeline Scheduling

    Tu, Renfu / Li, Zhengbing | Springer Verlag | 2023



    Advanced intelligent pipeline management technology

    Su, Huai ;Liao, Qi ;Zhang, Haoran | TIBKAT | 2023


    Urgency-Aware Scheduling Algorithm for Downlink Cognitive Long Term Evolution-Advanced

    Ramli, Huda Adibah Mohd / Isa, Farah Nadia Mohd / Asnawi, Ani Liza et al. | IEEE | 2019


    Modeling Pipeline Driving Behaviors

    Zou, Xi / Levinson, David M. | Transportation Research Record | 2006