论文标题
一种基于人造蜜蜂殖民优化的方法，用于考虑成本效益的北极海上钻井支持舰队的尺寸和组成
An Artificial Bee Colony optimization-based approach for sizing and composition of Arctic offshore drilling support fleets considering cost-efficiency
论文作者
论文摘要
本文提出了一种基于优化的方法，用于考虑成本效率的北极海上钻井支持车队的尺寸和组成。该方法研究了与北极离岸钻探有关的主要职责类型：供应，牵引，锚固，备用，备用，溢油响应，消防和冰管理。该方法认为，意外事件的预期成本，单个支撑船的多功能性和冰管理的综合作用。该方法采用了基于人造蜂群算法的优化程序。正如案例研究所证明的那样，该方法可能有助于找到一系列具有成本效益的车队组成。一些获得的解决方案类似于相应的现实生活舰队，表明该方法原则上起作用。敏感性分析表明，考虑到意外事件的预期成本的考虑会显着影响所获得的解决方案，并且降低这些成本的投资可能会提高北极海上钻探支持车队的整体成本效益。
This article presents an optimization-based approach for sizing and composition of an Arctic offshore drilling support fleet considering cost-efficiency. The approach studies the main types of duties related to Arctic offshore drillings: supply, towing, anchor handling, standby, oil spill response, firefighting, and ice management. The approach considers the combined effect of the expected costs of accidental events, the versatility of individual support vessels, and ice management. The approach applies an Artificial Bee Colony algorithm-based optimization procedure. As demonstrated through case studies, the approach may help to find a range of cost-efficient fleet compositions. Some of the obtained solutions are similar to corresponding real-life fleets, indicating that the approach works in principle. Sensitivity analyses indicate that the consideration of the expected costs from accidental events significantly impacts the obtained solution, and that investments to reduce these costs may improve the overall cost-efficiency of an Arctic offshore drilling support fleet.
