A memetic algorithm with recovery scheme for nurse preference scheduling

Chun-Cheng Lin*, Jia Rong Kang, Tzu Hsuan Hsu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


The previous works on designing evolutionary algorithm for nurse preference scheduling problems hardly realized that too many strict constraints on nurse preferences adopted at the same time lead to infeasible solutions frequently during the computational process. Therefore, to efficiently handle infeasible solutions, this study proposes a memetic algorithm that incorporates the genetic algorithm, the recovery scheme, and the local search designed specifically for our nurse preference scheduling problem, which aims to maximize the total satisfaction of the nursing staff with their preference rights and interests, including each nursing staff member's preferences and preference priority ordering for work shifts and days-off, under the hard constraints of manpower demands and the number of days-off. Our experimental results for the case in a real hospital show that our nurse schedule not only fairly accomplishes the assignment of most nursing staff members to their preferred work shifts and days-off, but also satisfies all constraints.

Original languageEnglish
Pages (from-to)83-95
Number of pages13
JournalJournal of Industrial and Production Engineering
Issue number2
StatePublished - 17 Feb 2015


  • genetic algorithm
  • nurse scheduling
  • preference rank

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