Improved Squeaky Wheel Optimisation for Driver Scheduling

  • Uwe Aickelin
  • Edmund K. Burke
  • Jingpeng Li
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4193)


This paper presents a technique called Improved Squeaky Wheel Optimisation (ISWO) for driver scheduling problems. It improves the original Squeaky Wheel Optimisation’s (SWO) effectiveness and execution speed by incorporating two additional steps of Selection and Mutation which implement evolution within a single solution. In the ISWO, a cycle of Analysis-Selection-Mutation-Prioritization-Construction continues until stopping conditions are reached. The Analysis step first computes the fitness of a current solution to identify troublesome components. The Selection step then discards these troublesome components probabilistically by using the fitness measure, and the Mutation step follows to further discard a small number of components at random. After the above steps, an input solution becomes partial and thus the resulting partial solution needs to be repaired. The repair is carried out by using the Prioritization step to first produce priorities that determine an order by which the following Construction step then schedules the remaining components. Therefore, the optimisation in the ISWO is achieved by solution disruption, iterative improvement and an iterative constructive repair process performed. Encouraging experimental results are reported.


Schedule Problem Construction Step Nurse Rostering Nurse Schedule Solution Disruption 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Uwe Aickelin
    • 1
  • Edmund K. Burke
    • 1
  • Jingpeng Li
    • 1
  1. 1.School of Computer Science and Information TechnologyThe University of NottinghamNottinghamUnited Kingdom

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