机组排班的混合集合规划方法研究

机组成本是仅次于燃料成本的第二大直接运营成本,合理的进行机组人员排班对降低航空公司运营成本有着重要意义。然而,机组排班问题是复杂性非常高的组合优化问题,属于NP难题。本文在分析机组排班问题研究进展的基础上,采用混合集合规划方法,综合考虑多种约束,建立了更具有实用性的机组排班优化模型。本文将运筹学理论与业务逻辑相结合,设计了高效的求解策略。利用多组航空公司真实数据对模型进行测试,测试结果表明,模型可以在较短时间内有效求解达到实际应用规模的机组排班问题。

Mixed Set Programming for Crew Pairing

Crew costs are the second largest direct operating costs in an airline's expenses, only next to fuel costs. However, crew pairing is a highly constrained and complex problem, which makes it extremely difficult to find optimal solutions. In this paper, mixed set programming(MSP)is proposed for the first time to build the model. Quite different from mathematical programming, MSP supports global reasoning over a mixed domain of real numbers, integers, booleans, and sets. Set partitioning model and routing model are the core parts of our model. Computational test shows that problems of real-world size can be solved efficiently within reasonable time.