A hybrid AI approach for nurse rostering problem

  • Authors:

  • Haibing Li;Andrew Lim;Brian Rodrigues

  • Affiliations:

  • University Heights, Newark, NJ;HKUST, Clear Water Bay, Kowloon, Hong Kong;Singapore Management University

  • Venue:
  • Proceedings of the 2003 ACM symposium on Applied computing
  • Year:
  • 2003

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Abstract

This paper presents a hybrid AI approach for a class of overconstrained Nurse Rostering Problems. Our approach comes in two phases. The first phase solves a relaxed version of problem which only includes hard rules and part of nurses' requests for shifts. This involves using a forward checking algorithm with non-binary constraint propagation, variable ordering, random value ordering and compulsory backjumping. In the second phase, adjustments with descend local search and tabu search are applied to improved the solution. This is to satisfy the preference rules as far as possible. Experiments show that our approach is able to solve this class of problems well.