A neural network application in personnel scheduling

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalNot applicablepeer-review

21 Scopus Citations
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Detail(s)

Original languageEnglish
Pages (from-to)65-90
Journal / PublicationAnnals of Operations Research
Volume128
Issue number1-4
StatePublished - Apr 2004

Abstract

In this paper, we present and evaluate a neural network model for solving a typical personnel-scheduling problem, i.e. an airport ground staff rostering problem. Personnel scheduling problems are widely found in servicing and manufacturing industries. The inherent complexity of personnel scheduling problems has normally resulted in the development of integer programming-based models and various heuristic solution procedures. The neural network approach has been admitted as a promising alternative to solving a variety of combinatorial optimization problems. While few works relate neural network to applications of personnel scheduling problems, there is great theoretical and practical value in exploring the potential of this area. In this paper, we introduce a neural network model following a relatively new modeling approach to solve a real rostering case. We show how to convert a mixed integer programming formulation to a neural network model. We also provide the experiment results comparing the neural network method with three popular heuristics, i.e. simulated annealing, Tabu search and genetic algorithm. The computational study reveals some potential of neural networks in solving personnel scheduling problems.

Research Area(s)

  • Neural network, Personnel scheduling, Rostering

Citation Format(s)

A neural network application in personnel scheduling. / Hao, G.; Lai, K. K.; Tan, M.

In: Annals of Operations Research, Vol. 128, No. 1-4, 04.2004, p. 65-90.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalNot applicablepeer-review