The paper aims to schedule check-in staff with hierarchical skills as well as day and night shifts in weekly rotation.That shift ensures staff work at day in a week and at night for the next week.The existing approach...The paper aims to schedule check-in staff with hierarchical skills as well as day and night shifts in weekly rotation.That shift ensures staff work at day in a week and at night for the next week.The existing approaches do not deal with the shift constraint.To address this,the proposed algorithm firstly guarantees the day and night shifts by designing a data copy tactic,and then introduces two algorithms to generate staff assignment in a polynomial time.The first algorithm is to yield an initial solution efficiently,whereas the second incrementally updates that solution to cut off working hours.The key idea of the two algorithms is to utilize a block Gibbs sampling with replacement to simultaneously exchange multiple staff assignment.Experimental results indicate that the proposed algorithm reduces at least 15.6 total working hours than the baselines.展开更多
基金the Natural Science Foundation of Tianjin(No.18JCYBJC85100)The Civil Aviation Key Technologies R&D Program of China(No.MHRD20140105)+1 种基金the Ministry of Education in China(MOE)Project of Humanities and Social Sciences(No.19YJA630046)the Open Project from Key Laboratory of Artificial Intelligence for Airlines,CAAC.
文摘The paper aims to schedule check-in staff with hierarchical skills as well as day and night shifts in weekly rotation.That shift ensures staff work at day in a week and at night for the next week.The existing approaches do not deal with the shift constraint.To address this,the proposed algorithm firstly guarantees the day and night shifts by designing a data copy tactic,and then introduces two algorithms to generate staff assignment in a polynomial time.The first algorithm is to yield an initial solution efficiently,whereas the second incrementally updates that solution to cut off working hours.The key idea of the two algorithms is to utilize a block Gibbs sampling with replacement to simultaneously exchange multiple staff assignment.Experimental results indicate that the proposed algorithm reduces at least 15.6 total working hours than the baselines.
