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Ant colony optimization-based algorithm for airline crew scheduling problem

机译:基于蚁群优化的机组人员调度问题算法

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摘要

Airline crew scheduling is an NP-hard constrained combinatorial optimization problem, and an effective crew scheduling system is essential for reducing operating costs in the airline industry. Ant colony optimization algorithm (ACO) has successfully applied to solve many difficult and classical optimization problems especially on traveling salesman problems (TSP). Therefore, this paper formulated airline crew scheduling problem as Traveling Salesman Problem and then introduce ant colony optimization algorithm to solve it. Performance was evaluated by performing computational tests regarding real cases as the test problems. The results showed that ACO-based algorithm can be potential technique for airline crew scheduling.
机译:航空公司的人员调度是一个NP约束受限的组合优化问题,有效的人员调度系统对于降低航空业的运营成本至关重要。蚁群优化算法(ACO)已成功应用于解决许多困难和经典的优化问题,尤其是在旅行商问题(TSP)上。因此,本文将航空公司的机组调度问题表述为旅行商问题,然后引入蚁群算法进行求解。通过执行将实际案例作为测试问题的计算测试来评估性能。结果表明,基于ACO的算法可能是航空公司机组调度的潜在技术。

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