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- 改进民航乘务员培养模式的思考
- 作者： 刘颖 来源： 四川劳动保障 年份： 2023 文献类型 ： 期刊 关键词： 高质量 校企合作 发展路径 乘务专业 培养模式 乘务员
- 描述： 通过讨论校企合作模式下民航乘务员的培养，在民航乘务员培养模式上找到更有利的方向，不断改进、优化培养思路，可以提升民航乘务员培养质量。民航乘务员培养需求现状民航乘务员具有专业鲜明的职业导向性，其主要
- 我国通用航空维修人才培养模式探索
- 作者： 许冀威 罗立 来源： 滨州学院学报 年份： 2019 文献类型 ： 期刊 关键词： 维修人才 通用航空 执照 培养模式 航空安全 市场需求
- 描述： 近年来,我国通用航空高速发展,但作为通用航空安全保障的维修人员在数量、工程技术能力、对相关适航法规的熟悉程度都不能满足现阶段通航发展的需要。通过对中国通航维修人才结构及培训体系现状进行剖析,找出问题根源,探索具有通航特点、面向通航需求的维修人才培养模式,从而为通用航空器的运行安全及通航的健康发展贡献力量。
- 我国通用航空维修人才培养模式探索
- 作者： 许冀威 罗立 来源： 滨州学院学报 年份： 2019 文献类型 ： 期刊 关键词： 维修人才 通用航空 执照 培养模式 航空安全 市场需求
- 描述： 近年来,我国通用航空高速发展,但作为通用航空安全保障的维修人员在数量、工程技术能力、对相关适航法规的熟悉程度都不能满足现阶段通航发展的需要。通过对中国通航维修人才结构及培训体系现状进行剖析,找出问题根源,探索具有通航特点、面向通航需求的维修人才培养模式,从而为通用航空器的运行安全及通航的健康发展贡献力量。
- Crew recovery optimization with deep learning and column generation for sustainable airline operation management
- 作者： Ahmet Herekoğlu Özgür Kabak 来源： Annals of Operations Research 年份： 2023 文献类型 ： 期刊 关键词： Artificial generation Crew disruptions Airline learning recovery Management Machine intelligence problem optimization Column Sustainability AutoML Sustainable Business
- 描述： In today’s competitive marketplace, businesses face the ongoing challenge of meeting evolving customer demands while maintaining sustainable practices. For airlines, sustainability is a critical consideration that involves optimizing resource usage. This study addresses the crew recovery problem, an essential aspect of building sustainable business models for airlines. The primary objective is to minimize costs associated with crew disruptions while considering constraints, including flight time limitations. Recovery strategies, realized through actions known as recovery actions, play a pivotal role in addressing crew disruptions. Leveraging historical data, learning-based approaches have the potential to enhance algorithms for large-scale optimization problems. They provide insights that may be overlooked through traditional methods, improving the success of the recovery process. This study presents a column generation-based solution approach for the crew recovery problem, utilizing a customized deep learning model to provide recovery actions as inputs. The methodology is applied to a major European airline company. The results indicate that the model, supported by deep learning outputs, outperforms traditional methods in terms of solution quality and efficiency.
- Crew recovery optimization with deep learning and column generation for sustainable airline operation management
- 作者： Ahmet Herekoğlu Özgür Kabak 来源： Annals of Operations Research 年份： 2023 文献类型 ： 期刊 关键词： Artificial generation Crew disruptions Airline learning recovery Management Machine intelligence problem optimization Column Sustainability AutoML Sustainable Business
- 描述： In today’s competitive marketplace, businesses face the ongoing challenge of meeting evolving customer demands while maintaining sustainable practices. For airlines, sustainability is a critical consideration that involves optimizing resource usage. This study addresses the crew recovery problem, an essential aspect of building sustainable business models for airlines. The primary objective is to minimize costs associated with crew disruptions while considering constraints, including flight time limitations. Recovery strategies, realized through actions known as recovery actions, play a pivotal role in addressing crew disruptions. Leveraging historical data, learning-based approaches have the potential to enhance algorithms for large-scale optimization problems. They provide insights that may be overlooked through traditional methods, improving the success of the recovery process. This study presents a column generation-based solution approach for the crew recovery problem, utilizing a customized deep learning model to provide recovery actions as inputs. The methodology is applied to a major European airline company. The results indicate that the model, supported by deep learning outputs, outperforms traditional methods in terms of solution quality and efficiency.