选择(遗传算法)
海底管道
海洋工程
环境科学
计算机科学
地质学
工程类
海洋学
人工智能
作者
Ivica Skoko,Zvonimir Lušić,Zaloa Sanchez–Varela,Zlatko Boko
摘要
Over the past century, with an accelerated increase in world energy demand, oil remained the most intriguing energy source, while oil exploration and production evolved from an onshore to an offshore exploration and production facility. In logistic and operational planning, the supply of offshore installations is the primary dependent of offshore supply vessels (OSVs). OSVs are classified into two main specialized groups, Anchor Handling Tug Supply (AHTS) and Platform Supply Vessels (PSVs). The establishment and maintenance of offshore oil installations require considerable financial resources for the hire of OSVs, which increases the oil exploration and production operator’s overall budget. Planning the offshore fleet structure aims to reduce expenses and increase the utilization of OSVs. This work will analyze the actual data of the southwestern African offshore market based on 24/7 working time and the use analysis of marine activities to define the parameters of the offshore fleet structure. The research results will be used to develop a methodology for modeling the optimal infrastructure of the offshore fleet. With statistical data of all support vessels’ activities and the use of linear programming (LP), it is possible to determine the vessel’s employment pattern and the optimal fleet structure by type and number of OSVs.
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