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Particle swarm optimization algorithm for solving airline crew scheduling problem

机译:粒子群优化算法解决机组人员调度问题

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In air transport, the cost related to crew members presents one of the most important cost supported by airline companies. The objective of the crew scheduling problem is to determine a minimum-cost set of pairings so that every flight leg is assigned a qualified crew and every pairing satisfies the set of applicable work rules. In this paper, we propose a solution for the crew scheduling problem with Particle Swarm Optimization (PSO) algorithm, this solution approach is compared with the Genetic Algorithm (GA) for both crew pairing and crew assignment problems which are the two part of crew scheduling problem.
机译:在航空运输中,与机组人员相关的成本是航空公司所支持的最重要的成本之一。机组调度问题的目的是确定一组最低成本的配对,以便为每个飞行航段分配合格的机组,并且每个配对均满足该套适用的工作规则。在本文中,我们提出了一种使用粒子群优化(PSO)算法解决机组调度问题的解决方案,将该解决方案与遗传算法(GA)进行了比较,以解决机组配对和机组分配问题,这是机组调度的两个组成部分问题。

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