Abstract
Many real-life problems are dynamic, with changes in the problem definition occurring after a solution to the initial formulation has been reached. A minimal perturbation problem incorporates these changes, along with the initial solution, as a new problem whose solution must be as close as possible to the initial solution. A new iterative forward search algorithm is proposed to solve minimal perturbation problems. Significant improvements to the solution quality are achieved by including new conflict-based statistics in this algorithm. The proposed methods were applied to find a new solution to an existing large scale class timetabling problem at Purdue University, incorporating the initial solution and additional input changes.
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Müller, T., Rudová, H., Barták, R. (2005). Minimal Perturbation Problem in Course Timetabling. In: Burke, E., Trick, M. (eds) Practice and Theory of Automated Timetabling V. PATAT 2004. Lecture Notes in Computer Science, vol 3616. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11593577_8
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DOI: https://doi.org/10.1007/11593577_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30705-1
Online ISBN: 978-3-540-32421-8
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