Bi-objective offshore supply vessel planning with costs and persistence objectives

Bi-objective offshore supply vessel planning with costs and persistence objectives. Borthen, T., Loennechen, H., Fagerholt, K., Wang, X., & Vidal, T. Computers & Operations Research, 111:285-296, 2019.

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This paper introduces a bi-objective model for the offshore supply vessel planning problem (SVPP) in the oil & gas industry. The SVPP consists of determining a new weekly plan for sailing the platform supply vessels whenever the sailing plan needs revising due to some major events, such as the arrival or re- moval of drilling rigs, and demand increase or reduction in the current platforms. Apart from remaining cost-efficient, the new weekly plan is required to be persistent , i.e., exhibiting few changes from the pre- vious plan. To achieve this, we propose a bi-objective optimization framework that enables the planners to simultaneously take into account both costs and persistence-related objectives. The framework encom- passes a bi-objective SVPP model and a genetic search algorithm adapted from Borthen et al. (2018). We show that the proposed algorithm is able to provide high-quality solutions in reasonable time and has the decision support capability in real offshore operation planning.

@article{
 title = {Bi-objective offshore supply vessel planning with costs and persistence objectives},
 type = {article},
 year = {2019},
 pages = {285-296},
 volume = {111},
 websites = {https://www.sciencedirect.com/science/article/pii/S0305054819301741/pdfft?md5=6c42b3c9091f90784cc45756553906e7&pid=1-s2.0-S0305054819301741-main.pdf},
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 abstract = {This paper introduces a bi-objective model for the offshore supply vessel planning problem (SVPP) in the oil & gas industry. The SVPP consists of determining a new weekly plan for sailing the platform supply vessels whenever the sailing plan needs revising due to some major events, such as the arrival or re- moval of drilling rigs, and demand increase or reduction in the current platforms. Apart from remaining cost-efficient, the new weekly plan is required to be persistent , i.e., exhibiting few changes from the pre- vious plan. To achieve this, we propose a bi-objective optimization framework that enables the planners to simultaneously take into account both costs and persistence-related objectives. The framework encom- passes a bi-objective SVPP model and a genetic search algorithm adapted from Borthen et al. (2018). We show that the proposed algorithm is able to provide high-quality solutions in reasonable time and has the decision support capability in real offshore operation planning.},
 bibtype = {article},
 author = {Borthen, T. and Loennechen, H. and Fagerholt, K. and Wang, X. and Vidal, T.},
 doi = {10.1016/j.cor.2019.06.014},
 journal = {Computers & Operations Research}
}

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